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README.md
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@@ -7,6 +7,38 @@ This LoRA trained for 3 epochs and has been converted to int4 via GPTQ method. S
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https://github.com/qwopqwop200/GPTQ-for-LLaMa
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--
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license: other
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---
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https://github.com/qwopqwop200/GPTQ-for-LLaMa
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# Usage
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1. Run manually through GPTQ
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2. (More setup but better UI) - Use the [text-generation-webui](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model#4-bit-mode). Make sure to follow the installation steps first [here](https://github.com/oobabooga/text-generation-webui#installation) before adding GPTQ support.
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**Note that a recent code change in GPTQ broke functionality for GPTQ in general, so please follow [these instructions](https://huggingface.co/elinas/alpaca-30b-lora-int4/discussions/2#641a38d5f1ad1c1173d8f192) to fix the issue!**
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Since this is instruction tuned, for best results, use the following format for inference:
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```
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### Instruction:
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your-prompt
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### Response:
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```
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If you want deterministic results, turn off sampling. You can turn it off in the webui by unchecking `do_sample`.
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For cai-chat mode, you won't want to use instruction prompting, rather create a character and set sampler settings. Here is an example of settings that work well for me:
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```
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do_sample=True
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temperature=0.95
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top_p=1
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typical_p=1
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repetition_penalty=1.1
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top_k=40
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num_beams=1
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penalty_alpha=0
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min_length=0
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length_penalty=1
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no_repeat_ngram_size=0
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early_stopping=False
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```
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You can then save this as a `.txt` file in the `presets` folder.
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--
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license: other
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---
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