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import gradio as gr |
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import spaces |
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import torch |
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import transformers |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "meta-llama/Meta-Llama-3-8B-Instruct" |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model_name, |
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model_kwargs={"torch_dtype": torch.bfloat16}, |
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device="cpu", |
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) |
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@spaces.GPU |
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def chat_function(message, history, system_prompt,max_new_tokens,temperature): |
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messages = [ |
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{"role": "system", "content": system_prompt}, |
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{"role": "user", "content": message}, |
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] |
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prompt = pipeline.tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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) |
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terminators = [ |
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pipeline.tokenizer.eos_token_id, |
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pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>") |
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] |
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temp = temperature + 0.1 |
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outputs = pipeline( |
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prompt, |
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max_new_tokens=max_new_tokens, |
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eos_token_id=terminators, |
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do_sample=True, |
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temperature=temp, |
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top_p=0.9, |
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) |
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return outputs[0]["generated_text"][len(prompt):] |
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gr.ChatInterface( |
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chat_function, |
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chatbot=gr.Chatbot(height=400), |
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textbox=gr.Textbox(placeholder="Enter message here", container=False, scale=7), |
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title="Meta-Llama-3-8B-Instruct", |
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description=""" |
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To Learn about Fine-tuning Llama-3-8B, Check https://exnrt.com/blog/ai/finetune-llama3-8b/. |
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""", |
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additional_inputs=[ |
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gr.Textbox("You are helpful AI.", label="System Prompt"), |
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gr.Slider(512, 4096, label="Max New Tokens"), |
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gr.Slider(0, 1, label="Temperature") |
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] |
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).launch() |
