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--- |
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license: apache-2.0 |
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datasets: |
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- cerebras/SlimPajama-627B |
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- bigcode/starcoderdata |
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- HuggingFaceH4/ultrachat_200k |
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- HuggingFaceH4/ultrafeedback_binarized |
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language: |
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- en |
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inference: false |
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--- |
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Optimum quantization using the command: |
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```bash |
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optimum-cli inc quantize --model TinyLlama/TinyLlama-1.1B-Chat-v1.0 --output ./TinyLlama |
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``` |
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Usage example: |
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```python |
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from optimum.intel import INCModelForCausalLM |
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from transformers import AutoTokenizer, pipeline, AutoModelForCausalLM |
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import torch |
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model_id = "Mihaiii/TinyLlama-1.1B-Chat-v1.0-optimum-intel" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = INCModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16) |
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|
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer) |
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messages = [ |
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{ |
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"role": "system", |
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"content": "You are a friendly chatbot who always responds in the style of a pirate", |
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}, |
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{"role": "user", "content": "How many helicopters can a human eat in one sitting?"}, |
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] |
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prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.0001, repetition_penalty=1.2) |
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print(outputs[0]["generated_text"]) |
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``` |