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--- |
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tags: |
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- autotrain |
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- text-generation-inference |
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- text-generation |
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- peft |
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library_name: transformers |
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base_model: meta-llama/Llama-3.2-1B-Instruct |
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widget: |
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- messages: |
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- role: user |
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content: What is your favorite condiment? |
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license: other |
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datasets: |
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- jeremierostan/restorative_practices |
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--- |
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# Model Trained Using AutoTrain |
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This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain). |
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# Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_path = "PATH_TO_THIS_REPO" |
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tokenizer = AutoTokenizer.from_pretrained(model_path) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_path, |
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device_map="auto", |
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torch_dtype='auto' |
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).eval() |
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# Prompt content: "hi" |
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messages = [ |
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{"role": "user", "content": "hi"} |
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] |
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input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt') |
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output_ids = model.generate(input_ids.to('cuda')) |
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response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True) |
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# Model response: "Hello! How can I assist you today?" |
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print(response) |
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``` |
