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--- |
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tags: |
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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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widget: |
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- messages: |
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- role: user |
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content: Translate the text 'Bonjour, comment allez-vous?' from French to English. |
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datasets: |
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- tatsu-lab/alpaca |
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metrics: |
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- accuracy |
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pipeline_tag: text-generation |
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license: cc-by-nc-4.0 |
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inference: false |
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--- |
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## LAI-Paca-7b |
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Instruction Fine-Tune of Mistral with the Alpaca dataset for instructions. It should primarily be used for API calls for tools, such as making a call to obtain a title for a song generated by a music generation AI based on a provided prompt or other applications. |
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## Notice |
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Please remember that the uploaded model is a adapter model. |
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<br> |
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It should be used in the Alpaca format. |
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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 = "Artples/LAI-Paca-7b" |
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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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``` |
