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  1. LICENSE +201 -0
  2. Llama-3-8B-Instruct-Coder-adapter/README.md +25 -0
  3. Llama-3-8B-Instruct-Coder-adapter/adapter_config.json +33 -0
  4. Llama-3-8B-Instruct-Coder-adapter/adapter_model.safetensors +3 -0
  5. Llama-3-8B-Instruct-Coder-adapter/generation_config.json +9 -0
  6. Llama-3-8B-Instruct-Coder-adapter/special_tokens_map.json +23 -0
  7. Llama-3-8B-Instruct-Coder-adapter/tokenizer.json +0 -0
  8. Llama-3-8B-Instruct-Coder-adapter/tokenizer_config.json +2064 -0
  9. Llama-3-SauerkrautLM-8b-Instruct-adapter/README.md +25 -0
  10. Llama-3-SauerkrautLM-8b-Instruct-adapter/adapter_config.json +33 -0
  11. Llama-3-SauerkrautLM-8b-Instruct-adapter/adapter_model.safetensors +3 -0
  12. Llama-3-SauerkrautLM-8b-Instruct-adapter/generation_config.json +9 -0
  13. Llama-3-SauerkrautLM-8b-Instruct-adapter/special_tokens_map.json +5 -0
  14. Llama-3-SauerkrautLM-8b-Instruct-adapter/tokenizer.json +0 -0
  15. Llama-3-SauerkrautLM-8b-Instruct-adapter/tokenizer_config.json +2062 -0
  16. Llama-3-Smaug-8B-adapter/README.md +25 -0
  17. Llama-3-Smaug-8B-adapter/adapter_config.json +33 -0
  18. Llama-3-Smaug-8B-adapter/adapter_model.safetensors +3 -0
  19. Llama-3-Smaug-8B-adapter/generation_config.json +6 -0
  20. Llama-3-Smaug-8B-adapter/special_tokens_map.json +23 -0
  21. Llama-3-Smaug-8B-adapter/tokenizer.json +0 -0
  22. Llama-3-Smaug-8B-adapter/tokenizer_config.json +2064 -0
  23. Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/README.md +25 -0
  24. Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/adapter_config.json +33 -0
  25. Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/adapter_model.safetensors +3 -0
  26. Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/generation_config.json +6 -0
  27. Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/special_tokens_map.json +16 -0
  28. Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/tokenizer.json +0 -0
  29. Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/tokenizer_config.json +2062 -0
  30. config.json +31 -0
  31. configuration_kraken_lora.py +8 -0
  32. kraken_model/config.json +39 -0
  33. kraken_model/generation_config.json +4 -0
  34. kraken_model/model-00001-of-00004.safetensors +3 -0
  35. kraken_model/model-00002-of-00004.safetensors +3 -0
  36. kraken_model/model-00003-of-00004.safetensors +3 -0
  37. kraken_model/model-00004-of-00004.safetensors +3 -0
  38. kraken_model/model.safetensors.index.json +589 -0
  39. llama-3-sqlcoder-8b-adapter/README.md +25 -0
  40. llama-3-sqlcoder-8b-adapter/adapter_config.json +33 -0
  41. llama-3-sqlcoder-8b-adapter/adapter_model.safetensors +3 -0
  42. llama-3-sqlcoder-8b-adapter/generation_config.json +12 -0
  43. llama-3-sqlcoder-8b-adapter/special_tokens_map.json +16 -0
  44. llama-3-sqlcoder-8b-adapter/tokenizer.json +0 -0
  45. llama-3-sqlcoder-8b-adapter/tokenizer_config.json +2062 -0
  46. modeling_kraken_lora.py +86 -0
  47. requirements.txt +85 -0
  48. tokenizer_template_switch.py +95 -0
LICENSE ADDED
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Llama-3-8B-Instruct-Coder-adapter/README.md ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model:
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+ - meta-llama/Meta-Llama-3-8B-Instruct
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+ - rombodawg/Llama-3-8B-Instruct-Coder
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+ library_name: transformers
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+ tags:
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+ - mergekit
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+ - peft
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+
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+ ---
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+ # Untitled LoRA Model (1)
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+
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+ This is a LoRA extracted from a language model. It was extracted using [mergekit](https://github.com/arcee-ai/mergekit).
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+
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+ ## LoRA Details
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+
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+ This LoRA adapter was extracted from [rombodawg/Llama-3-8B-Instruct-Coder](https://huggingface.co/rombodawg/Llama-3-8B-Instruct-Coder) and uses [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base.
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+
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+ ### Parameters
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+
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+ The following command was used to extract this LoRA adapter:
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+
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+ ```sh
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+ mergekit-extract-lora meta-llama/Meta-Llama-3-8B-Instruct rombodawg/Llama-3-8B-Instruct-Coder OUTPUT_PATH --no-lazy-unpickle --rank=32 --device=cuda
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+ ```
Llama-3-8B-Instruct-Coder-adapter/adapter_config.json ADDED
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+ {
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+ "alpha_pattern": {},
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+ "auto_mapping": null,
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+ "base_model_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
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+ "bias": "none",
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+ "fan_in_fan_out": false,
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "layers_pattern": null,
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+ "layers_to_transform": null,
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+ "loftq_config": {},
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+ "lora_alpha": 32,
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+ "lora_dropout": 0,
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+ "megatron_config": null,
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+ "megatron_core": "megatron.core",
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+ "modules_to_save": null,
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+ "peft_type": "LORA",
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+ "r": 32,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "lm_head",
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+ "gate_proj",
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+ "down_proj",
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+ "o_proj",
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+ "v_proj",
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+ "q_proj",
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+ "up_proj",
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+ "k_proj"
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+ ],
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+ "task_type": "CAUSAL_LM",
32
+ "use_rslora": false
33
+ }
Llama-3-8B-Instruct-Coder-adapter/adapter_model.safetensors ADDED
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Llama-3-8B-Instruct-Coder-adapter/generation_config.json ADDED
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+ {
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+ "bos_token_id": 128000,
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+ 128009
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+ ],
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+ "transformers_version": "4.40.1"
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+ }
Llama-3-8B-Instruct-Coder-adapter/special_tokens_map.json ADDED
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+ "single_word": false
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+ }
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+ }
Llama-3-8B-Instruct-Coder-adapter/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
Llama-3-8B-Instruct-Coder-adapter/tokenizer_config.json ADDED
@@ -0,0 +1,2064 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128222": {
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+ "content": "<|reserved_special_token_217|>",
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+ "lstrip": false,
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+ "single_word": false,
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+ "special": true
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+ "single_word": false,
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+ "special": true
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+ },
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+ "special": true
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+ "content": "<|reserved_special_token_220|>",
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+ "special": true
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+ "special": true
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+ },
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+ "single_word": false,
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+ "special": true
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+ "content": "<|reserved_special_token_223|>",
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1832
+ "single_word": false,
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+ "special": true
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+ },
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1836
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+ "single_word": false,
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+ "special": true
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+ },
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1844
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+ "lstrip": false,
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+ "special": true
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+ },
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+ "content": "<|reserved_special_token_226|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
1856
+ "single_word": false,
1857
+ "special": true
1858
+ },
1859
+ "128232": {
1860
+ "content": "<|reserved_special_token_227|>",
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+ "lstrip": false,
1862
+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128233": {
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+ "content": "<|reserved_special_token_228|>",
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+ "lstrip": false,
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+ "single_word": false,
1873
+ "special": true
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+ },
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+ "special": true
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+ },
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+ "single_word": false,
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+ "special": true
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+ },
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+ "single_word": false,
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+ "special": true
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+ },
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+ "single_word": false,
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+ "special": true
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+ "single_word": false,
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+ "special": true
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+ },
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+ "special": true
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+ "special": true
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+ },
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+ "special": true
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+ },
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+ "128242": {
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+ "content": "<|reserved_special_token_237|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128243": {
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+ "lstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128244": {
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+ "lstrip": false,
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+ "special": true
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+ },
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+ "128245": {
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+ "special": true
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+ "special": true
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+ },
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+ "128247": {
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+ "rstrip": false,
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+ "single_word": false,
1985
+ "special": true
1986
+ },
1987
+ "128248": {
1988
+ "content": "<|reserved_special_token_243|>",
1989
+ "lstrip": false,
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
1995
+ "128249": {
1996
+ "content": "<|reserved_special_token_244|>",
1997
+ "lstrip": false,
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+ "single_word": false,
2001
+ "special": true
2002
+ },
2003
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2004
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2005
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+ "special": true
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+ },
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+ "128251": {
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+ "special": true
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+ },
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+ "128252": {
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+ "single_word": false,
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+ },
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+ "content": "<|reserved_special_token_248|>",
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+ "special": true
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+ },
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+ "content": "<|reserved_special_token_249|>",
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2041
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+ },
2043
+ "128255": {
2044
+ "content": "<|reserved_special_token_250|>",
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+ "rstrip": false,
2048
+ "single_word": false,
2049
+ "special": true
2050
+ }
2051
+ },
2052
+ "bos_token": "<|begin_of_text|>",
2053
+ "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|end_of_text|>",
2056
+ "model_input_names": [
2057
+ "input_ids",
2058
+ "attention_mask"
2059
+ ],
2060
+ "model_max_length": 8192,
2061
+ "pad_token": "<|end_of_text|>",
2062
+ "padding_side": "left",
2063
+ "tokenizer_class": "PreTrainedTokenizerFast"
2064
+ }
Llama-3-SauerkrautLM-8b-Instruct-adapter/README.md ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model:
3
+ - meta-llama/Meta-Llama-3-8B-Instruct
4
+ - VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
5
+ library_name: transformers
6
+ tags:
7
+ - mergekit
8
+ - peft
9
+
10
+ ---
11
+ # Untitled LoRA Model (1)
12
+
13
+ This is a LoRA extracted from a language model. It was extracted using [mergekit](https://github.com/arcee-ai/mergekit).
14
+
15
+ ## LoRA Details
16
+
17
+ This LoRA adapter was extracted from [VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct) and uses [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base.
18
+
19
+ ### Parameters
20
+
21
+ The following command was used to extract this LoRA adapter:
22
+
23
+ ```sh
24
+ mergekit-extract-lora meta-llama/Meta-Llama-3-8B-Instruct VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct OUTPUT_PATH --no-lazy-unpickle --rank=32 --device=cuda
25
+ ```
Llama-3-SauerkrautLM-8b-Instruct-adapter/adapter_config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 32,
13
+ "lora_dropout": 0,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 32,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "v_proj",
23
+ "gate_proj",
24
+ "k_proj",
25
+ "q_proj",
26
+ "down_proj",
27
+ "up_proj",
28
+ "o_proj",
29
+ "lm_head"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_rslora": false
33
+ }
Llama-3-SauerkrautLM-8b-Instruct-adapter/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a1e5f741f0578465d7333e97935b7564280b560fa29223f8cb518a2d9eb1af41
3
+ size 176303496
Llama-3-SauerkrautLM-8b-Instruct-adapter/generation_config.json ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 128000,
4
+ "eos_token_id": [
5
+ 128001,
6
+ 128009
7
+ ],
8
+ "transformers_version": "4.40.0"
9
+ }
Llama-3-SauerkrautLM-8b-Instruct-adapter/special_tokens_map.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "bos_token": "<|begin_of_text|>",
3
+ "eos_token": "<|end_of_text|>",
4
+ "pad_token": "<|end_of_text|>"
5
+ }
Llama-3-SauerkrautLM-8b-Instruct-adapter/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
Llama-3-SauerkrautLM-8b-Instruct-adapter/tokenizer_config.json ADDED
@@ -0,0 +1,2062 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "128000": {
4
+ "content": "<|begin_of_text|>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
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+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "128001": {
12
+ "content": "<|end_of_text|>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "128002": {
20
+ "content": "<|reserved_special_token_0|>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "128003": {
28
+ "content": "<|reserved_special_token_1|>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "128004": {
36
+ "content": "<|reserved_special_token_2|>",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ },
43
+ "128005": {
44
+ "content": "<|reserved_special_token_3|>",
45
+ "lstrip": false,
46
+ "normalized": false,
47
+ "rstrip": false,
48
+ "single_word": false,
49
+ "special": true
50
+ },
51
+ "128006": {
52
+ "content": "<|start_header_id|>",
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+ }
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+ },
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+ "bos_token": "<|begin_of_text|>",
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+ "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
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+ "clean_up_tokenization_spaces": true,
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+ "eos_token": "<|eot_id|>",
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+ "model_input_names": [
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+ "input_ids",
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+ "attention_mask"
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+ ],
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+ "model_max_length": 1000000000000000019884624838656,
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+ "tokenizer_class": "PreTrainedTokenizerFast"
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+ }
Llama-3-Smaug-8B-adapter/README.md ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model:
3
+ - meta-llama/Meta-Llama-3-8B-Instruct
4
+ - abacusai/Llama-3-Smaug-8B
5
+ library_name: transformers
6
+ tags:
7
+ - mergekit
8
+ - peft
9
+
10
+ ---
11
+ # Untitled LoRA Model (1)
12
+
13
+ This is a LoRA extracted from a language model. It was extracted using [mergekit](https://github.com/arcee-ai/mergekit).
14
+
15
+ ## LoRA Details
16
+
17
+ This LoRA adapter was extracted from [abacusai/Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B) and uses [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base.
18
+
19
+ ### Parameters
20
+
21
+ The following command was used to extract this LoRA adapter:
22
+
23
+ ```sh
24
+ mergekit-extract-lora meta-llama/Meta-Llama-3-8B-Instruct abacusai/Llama-3-Smaug-8B OUTPUT_PATH --no-lazy-unpickle --rank=32 --device=cuda
25
+ ```
Llama-3-Smaug-8B-adapter/adapter_config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 32,
13
+ "lora_dropout": 0,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 32,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "k_proj",
23
+ "gate_proj",
24
+ "o_proj",
25
+ "down_proj",
26
+ "up_proj",
27
+ "v_proj",
28
+ "q_proj",
29
+ "lm_head"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_rslora": false
33
+ }
Llama-3-Smaug-8B-adapter/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadcdb97fb08bdc44376312f1218620161b15fb20f720b3525960684c47217ca
3
+ size 176303496
Llama-3-Smaug-8B-adapter/generation_config.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 128000,
4
+ "eos_token_id": 128001,
5
+ "transformers_version": "4.37.2"
6
+ }
Llama-3-Smaug-8B-adapter/special_tokens_map.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "bos_token": {
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+ "content": "<|begin_of_text|>",
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+ "single_word": false
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+ }
23
+ }
Llama-3-Smaug-8B-adapter/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
Llama-3-Smaug-8B-adapter/tokenizer_config.json ADDED
@@ -0,0 +1,2064 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Meta-Llama-3-8B-Instruct-function-calling-json-mode-adapter/README.md ADDED
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1
+ ---
2
+ base_model:
3
+ - meta-llama/Meta-Llama-3-8B-Instruct
4
+ - hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode
5
+ library_name: transformers
6
+ tags:
7
+ - mergekit
8
+ - peft
9
+
10
+ ---
11
+ # Untitled LoRA Model (1)
12
+
13
+ This is a LoRA extracted from a language model. It was extracted using [mergekit](https://github.com/arcee-ai/mergekit).
14
+
15
+ ## LoRA Details
16
+
17
+ This LoRA adapter was extracted from [hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode](https://huggingface.co/hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode) and uses [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base.
18
+
19
+ ### Parameters
20
+
21
+ The following command was used to extract this LoRA adapter:
22
+
23
+ ```sh
24
+ mergekit-extract-lora meta-llama/Meta-Llama-3-8B-Instruct hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode OUTPUT_PATH --no-lazy-unpickle --rank=32 --device=cuda
25
+ ```
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_rslora": false
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+ }
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+ oid sha256:a079138abd3cb5967b2cb776e8f8329d76f96e1d2840fd3b91d2abf3b1f72743
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+ size 176303496
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+ }
configuration_kraken_lora.py ADDED
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+ from transformers import PretrainedConfig
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+
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+ class KrakenConfig(PretrainedConfig):
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+ model_type = "kraken"
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+
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+ def __init__(self, config_dict=None, **kwargs):
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+ super().__init__(**kwargs)
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+ self.config_dict = config_dict or {}
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llama-3-sqlcoder-8b-adapter/README.md ADDED
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1
+ ---
2
+ base_model:
3
+ - meta-llama/Meta-Llama-3-8B-Instruct
4
+ - defog/llama-3-sqlcoder-8b
5
+ library_name: transformers
6
+ tags:
7
+ - mergekit
8
+ - peft
9
+
10
+ ---
11
+ # Untitled LoRA Model (1)
12
+
13
+ This is a LoRA extracted from a language model. It was extracted using [mergekit](https://github.com/arcee-ai/mergekit).
14
+
15
+ ## LoRA Details
16
+
17
+ This LoRA adapter was extracted from [defog/llama-3-sqlcoder-8b](https://huggingface.co/defog/llama-3-sqlcoder-8b) and uses [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base.
18
+
19
+ ### Parameters
20
+
21
+ The following command was used to extract this LoRA adapter:
22
+
23
+ ```sh
24
+ mergekit-extract-lora meta-llama/Meta-Llama-3-8B-Instruct defog/llama-3-sqlcoder-8b OUTPUT_PATH --no-lazy-unpickle --rank=32 --device=cuda
25
+ ```
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+ "target_modules": [
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+ "gate_proj",
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_rslora": false
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+ }
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+ {
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+ }
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llama-3-sqlcoder-8b-adapter/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
llama-3-sqlcoder-8b-adapter/tokenizer_config.json ADDED
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+ },
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+ },
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+ "special": true
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+ "special": true
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+ },
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+ },
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+ },
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+ },
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+ },
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+ },
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+ "content": "<|reserved_special_token_232|>",
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+ "special": true
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+ "lstrip": false,
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+ "special": true
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+ },
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1930
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+ "content": "<|reserved_special_token_236|>",
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+ "content": "<|reserved_special_token_237|>",
1941
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+ "content": "<|reserved_special_token_239|>",
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1963
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1971
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+ "content": "<|reserved_special_token_241|>",
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1978
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1979
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1980
+ "content": "<|reserved_special_token_242|>",
1981
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+ },
1987
+ "128248": {
1988
+ "content": "<|reserved_special_token_243|>",
1989
+ "lstrip": false,
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+ "normalized": false,
1991
+ "rstrip": false,
1992
+ "single_word": false,
1993
+ "special": true
1994
+ },
1995
+ "128249": {
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+ "content": "<|reserved_special_token_244|>",
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+ "lstrip": false,
1998
+ "normalized": false,
1999
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128250": {
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+ "content": "<|reserved_special_token_245|>",
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+ "lstrip": false,
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+ "special": true
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+ },
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+ "128251": {
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+ "content": "<|reserved_special_token_246|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
2018
+ },
2019
+ "128252": {
2020
+ "content": "<|reserved_special_token_247|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "special": true
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+ },
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+ "128253": {
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+ "content": "<|reserved_special_token_248|>",
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+ "lstrip": false,
2030
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2031
+ "rstrip": false,
2032
+ "single_word": false,
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+ "special": true
2034
+ },
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+ "128254": {
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+ "content": "<|reserved_special_token_249|>",
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+ "lstrip": false,
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+ "special": true
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+ },
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+ "128255": {
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+ "content": "<|reserved_special_token_250|>",
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+ "lstrip": false,
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+ "normalized": false,
2047
+ "rstrip": false,
2048
+ "single_word": false,
2049
+ "special": true
2050
+ }
2051
+ },
2052
+ "bos_token": "<|begin_of_text|>",
2053
+ "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "model_input_names": [
2057
+ "input_ids",
2058
+ "attention_mask"
2059
+ ],
2060
+ "model_max_length": 1000000000000000019884624838656,
2061
+ "tokenizer_class": "PreTrainedTokenizerFast"
2062
+ }
modeling_kraken_lora.py ADDED
@@ -0,0 +1,86 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import torch
2
+ from transformers import PreTrainedModel, AutoTokenizer, AutoModelForCausalLM, AutoModelForSequenceClassification, TextClassificationPipeline
3
+ from configuration_kraken_lora import KrakenConfig
4
+ import tokenizer_template_switch
5
+ from peft import PeftModel, PeftConfig # Import necessary modules for LoRA
6
+
7
+ class KrakenForCausalLM(PreTrainedModel):
8
+ config_class = KrakenConfig
9
+
10
+ def __init__(self, config):
11
+ super().__init__(config)
12
+ self.tokenizers = {key: AutoTokenizer.from_pretrained(name, device_map="auto") for key, name in config.config_dict['tokenizers'].items()}
13
+ self.model = self.load_base_model(config.config_dict['models']['base'], config.config_dict['quantization']['base']) # Load only expert1 as the base model
14
+ self.lora_adapters = config.config_dict['lora_adapters'] # Load LoRA adapter paths
15
+ self.router_model = AutoModelForSequenceClassification.from_pretrained(config.config_dict['router'], trust_remote_code=True, device_map="auto")
16
+ self.tokenizer = AutoTokenizer.from_pretrained(config.config_dict['router'], trust_remote_code=True, device_map="auto")
17
+ self.router = TextClassificationPipeline(model=self.router_model, tokenizer=self.tokenizer)
18
+ self.models_indices = config.config_dict['class_indices']
19
+
20
+ def load_base_model(self, model_name, quantization):
21
+ if quantization == "8bit":
22
+ return AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, device_map="auto", load_in_8bit=True, torch_dtype="auto")
23
+ elif quantization == "4bit":
24
+ return AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, device_map="auto", load_in_4bit=True, torch_dtype="auto")
25
+ elif quantization == "awq":
26
+ return self.load_awq_model(model_name)
27
+ else:
28
+ return AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, device_map="auto", torch_dtype="auto")
29
+
30
+ def load_awq_model(self, name):
31
+ return AutoModelForCausalLM.from_pretrained(name, trust_remote_code=True, device_map="auto")
32
+
33
+ def load_lora_adapter(self, base_model, adapter_path):
34
+ print("Loading adapter: "+adapter_path)
35
+ return PeftModel.from_pretrained(base_model, adapter_path)
36
+
37
+ def tokenize_inputs(self, text, adapter_key):
38
+ return self.tokenizers[adapter_key](text, return_tensors="pt")
39
+
40
+ def determine_adapter(self, text):
41
+ prediction = self.router(text)[0]["label"]
42
+ model_decision_index = self.models_indices[prediction]
43
+ adapter_keys = ['lora_expert1', 'lora_expert2', 'lora_expert3', 'lora_expert4', 'lora_expert5']
44
+ return adapter_keys[model_decision_index]
45
+
46
+ def expert_tokenizer(self, text):
47
+ adapter_key = self.determine_adapter(text)
48
+ return self.tokenizers[adapter_key]
49
+
50
+
51
+ def generate(self, input_ids, **generate_kwargs):
52
+ # Tokenize the input_ids
53
+ text = self.tokenizer.batch_decode(input_ids, skip_special_tokens=False)[0]
54
+
55
+ msgs = tokenizer_template_switch.recover_chat_messages(text, self.tokenizer)
56
+ if msgs and msgs[0]['role'] == 'system' and msgs[0]['content']=='<|im_start|>system':
57
+ # Delete the first element
58
+ msgs.pop(0)
59
+ # Check if the last element has the role 'assistant'
60
+ if msgs and msgs[-1]['role'] == 'assistant':
61
+ # Delete the last element
62
+ msgs.pop()
63
+
64
+
65
+ # Determine the appropriate LoRA adapter
66
+ adapter_key = self.determine_adapter(text)
67
+ print(f"Choosing LoRA adapter for {adapter_key} ..")
68
+ # Load and apply the LoRA adapter to the base model (expert1)
69
+ lora_adapter_path = self.lora_adapters[adapter_key]
70
+ model_with_lora = self.load_lora_adapter(self.model, lora_adapter_path)
71
+
72
+ # Use the tokenizer for the selected expert to tokenize the inputs
73
+ mod_txt = self.tokenizers[adapter_key].apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
74
+ current_device = input_ids.device if isinstance(input_ids, torch.Tensor) else 'cpu'
75
+
76
+ # Tokenize accordingly to the best model
77
+
78
+ tok = self.tokenizers[adapter_key](mod_txt, return_tensors="pt")
79
+ tok_input_ids = tok.input_ids.to(current_device)
80
+ tok_attention_mask = tok.attention_mask.to(current_device)
81
+
82
+ # Generate text using the modified model
83
+ return model_with_lora.generate(tok_input_ids, attention_mask=tok_attention_mask, **generate_kwargs)
84
+
85
+
86
+
requirements.txt ADDED
@@ -0,0 +1,85 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ accelerate==0.27.2
2
+ aiohttp==3.9.5
3
+ aiosignal==1.3.1
4
+ appnope==0.1.4
5
+ asttokens==2.4.1
6
+ attrs==23.2.0
7
+ bitsandbytes==0.42.0
8
+ certifi==2024.2.2
9
+ charset-normalizer==3.3.2
10
+ comm==0.2.2
11
+ contourpy==1.2.1
12
+ cycler==0.12.1
13
+ datasets==2.19.1
14
+ debugpy==1.8.1
15
+ decorator==5.1.1
16
+ dill==0.3.8
17
+ et-xmlfile==1.1.0
18
+ executing==2.0.1
19
+ filelock==3.14.0
20
+ fonttools==4.51.0
21
+ frozenlist==1.4.1
22
+ fsspec==2024.3.1
23
+ huggingface-hub==0.23.0
24
+ idna==3.7
25
+ ipykernel==6.29.4
26
+ ipython==8.24.0
27
+ jedi==0.19.1
28
+ Jinja2==3.1.4
29
+ joblib==1.4.2
30
+ jupyter_client==8.6.1
31
+ jupyter_core==5.7.2
32
+ kiwisolver==1.4.5
33
+ MarkupSafe==2.1.5
34
+ matplotlib==3.9.0
35
+ matplotlib-inline==0.1.7
36
+ mpmath==1.3.0
37
+ multidict==6.0.5
38
+ multiprocess==0.70.16
39
+ nest-asyncio==1.6.0
40
+ networkx==3.3
41
+ numpy==1.26.4
42
+ openpyxl==3.1.2
43
+ packaging==24.0
44
+ pandas==2.2.2
45
+ parso==0.8.4
46
+ pexpect==4.9.0
47
+ pillow==10.3.0
48
+ platformdirs==4.2.2
49
+ prompt-toolkit==3.0.43
50
+ protobuf==5.26.1
51
+ psutil==5.9.8
52
+ ptyprocess==0.7.0
53
+ pure-eval==0.2.2
54
+ pyarrow==16.1.0
55
+ pyarrow-hotfix==0.6
56
+ Pygments==2.18.0
57
+ pyparsing==3.1.2
58
+ python-dateutil==2.9.0.post0
59
+ pytz==2024.1
60
+ PyYAML==6.0.1
61
+ pyzmq==26.0.3
62
+ rapidfuzz==3.9.0
63
+ regex==2024.5.15
64
+ requests==2.31.0
65
+ safetensors==0.4.3
66
+ scikit-learn==1.4.2
67
+ scipy==1.13.0
68
+ sentence-transformers==2.7.0
69
+ sentencepiece==0.2.0
70
+ six==1.16.0
71
+ stack-data==0.6.3
72
+ sympy==1.12
73
+ threadpoolctl==3.5.0
74
+ tokenizers==0.19.1
75
+ torch==2.3.0
76
+ tornado==6.4
77
+ tqdm==4.66.4
78
+ traitlets==5.14.3
79
+ transformers==4.41.0
80
+ typing_extensions==4.11.0
81
+ tzdata==2024.1
82
+ urllib3==2.2.1
83
+ wcwidth==0.2.13
84
+ xxhash==3.4.1
85
+ yarl==1.9.4
tokenizer_template_switch.py ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import re
2
+ from transformers import AutoTokenizer
3
+
4
+ def extract_separators(template):
5
+ """
6
+ Extracts separators used in the tokenization template.
7
+ """
8
+ # Adjust the regex to correctly match the specific pattern between '{{' and '+ message["content"] +'
9
+ pattern = r"\{\{\s*([^{}]+?)\s*\+ message\['content'\]"
10
+ matches = re.findall(pattern, template)
11
+ # Clean up any extra spaces and return the matches
12
+ separators = [match.strip() for match in matches]
13
+
14
+ if any("message['role']" in element for element in separators):
15
+ roles = ["system", "user", "assistant"]
16
+ separators_ = []
17
+ for role in roles:
18
+ separators_.append(separators[0].replace(" + message['role'] + ", role).replace("'",""))
19
+ return separators_
20
+
21
+ return separators
22
+
23
+ def detect_eos_token(jinja_template, tokenizer):
24
+ if "<|im_end|>" in jinja_template:
25
+ return "<|im_end|>"
26
+ if "</s>" in jinja_template:
27
+ return "</s>"
28
+ if "eos_token" in jinja_template:
29
+ return tokenizer.eos_token
30
+ else:
31
+ return "<|endoftext|>"
32
+
33
+ def recover_messages(formatted_message, separators, eos_token):
34
+ """
35
+ Recovers the original messages from the formatted message string.
36
+ """
37
+ # Split the formatted message using the end-of-string token
38
+ split_messages = formatted_message.split(eos_token)
39
+
40
+ # Remove the last empty string if it exists due to a trailing separator
41
+ if split_messages and split_messages[-1].strip() == '':
42
+ split_messages.pop()
43
+
44
+ # Prepare the list to hold the recovered messages
45
+ recovered_messages = []
46
+
47
+ # Define roles after the first message, alternating between "user" and "assistant"
48
+ alternate_roles = ["user", "assistant"]
49
+
50
+ # Iterate over the split messages
51
+ for index, message_content in enumerate(split_messages):
52
+ # Determine the role, starting with "system" for the first message
53
+ # then alternating between "user" and "assistant" for subsequent messages
54
+ if index == 0:
55
+ role = "system"
56
+ else:
57
+ role = alternate_roles[(index - 1) % 2]
58
+
59
+ # Clean the message content by removing leading/trailing whitespace and separators
60
+ clean_content = message_content.strip()
61
+ for separator in separators:
62
+ clean_content = clean_content.replace(separator.strip("'"), '', 1).strip()
63
+
64
+ # Append the cleaned message with its role to the list
65
+ recovered_messages.append({"role": role, "content": clean_content})
66
+
67
+ return recovered_messages
68
+
69
+ def recover_chat_messages(tokenized_chat, tokenizer):
70
+ """
71
+ Given a tokenized_chat string and a tokenizer, returns the list of message dictionaries.
72
+ """
73
+ jinja_template = tokenizer.chat_template
74
+ separators = extract_separators(jinja_template)
75
+ eos_token = eos_token = detect_eos_token(jinja_template, tokenizer)
76
+ recovered_messages = recover_messages(tokenized_chat, separators, eos_token)
77
+ return recovered_messages
78
+
79
+ # Example usage
80
+ if __name__ == "__main__":
81
+ checkpoint = "Qwen/Qwen1.5-0.5B"
82
+ tokenizer = AutoTokenizer.from_pretrained(checkpoint)
83
+
84
+ messages = [
85
+ {
86
+ "role": "system",
87
+ "content": "You are a friendly chatbot who always responds in the style of a pirate",
88
+ },
89
+ {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
90
+ ]
91
+ tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=False)
92
+ print(tokenized_chat)
93
+
94
+ recovered_messages = recover_chat_messages(tokenized_chat, tokenizer)
95
+ print(recovered_messages)