How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="NoaiGPT/MergedNoaigptUnslothLlama")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NoaiGPT/MergedNoaigptUnslothLlama")
model = AutoModelForCausalLM.from_pretrained("NoaiGPT/MergedNoaigptUnslothLlama")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
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language:

  • en pipeline_tag: text-generation tags:
  • facebook
  • meta
  • pytorch
  • llama
  • llama-3 license: llama3 extra_gated_prompt: >-

META LLAMA 3 COMMUNITY LICENSE AGREEMENT

Meta Llama 3 Version Release Date: April 18, 2024

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