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| import gradio as gr | |
| import os | |
| from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer | |
| from threading import Thread | |
| # Set an environment variable | |
| HF_TOKEN = os.environ.get("HF_TOKEN", None) | |
| DESCRIPTION = ''' | |
| <div> | |
| <h1 style="text-align: center;">AI Lawyer</h1> | |
| <p>This Space demonstrates the instruction-tuned model <a href="https://huggingface.co/StevenChen16/llama3-8b-Lawyer"><b>StevenChen16/llama3-8b-Lawyer</b></a>. This model is fine-tuned to provide legal information and assist with a wide range of legal questions. Feel free to ask anything!</p> | |
| </div> | |
| ''' | |
| LICENSE = """ | |
| <p/> | |
| --- | |
| Built with model "StevenChen16/Llama3-8B-Lawyer", based on "meta-llama/Meta-Llama-3-8B" | |
| """ | |
| PLACEHOLDER = """ | |
| <div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;"> | |
| <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">AI Lawyer</h1> | |
| <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Ask me anything about US and Canada law...</p> | |
| </div> | |
| """ | |
| css = """ | |
| h1 { | |
| text-align: center; | |
| display: block; | |
| } | |
| #duplicate-button { | |
| margin: auto; | |
| color: white; | |
| background: #1565c0; | |
| border-radius: 100vh; | |
| } | |
| """ | |
| # Load the tokenizer and model | |
| tokenizer = AutoTokenizer.from_pretrained("StevenChen16/llama3-8b-Lawyer") | |
| model = AutoModelForCausalLM.from_pretrained("StevenChen16/llama3-8b-Lawyer", device_map="auto") | |
| terminators = [ | |
| tokenizer.eos_token_id, | |
| tokenizer.convert_tokens_to_ids("") | |
| ] | |
| def chat_llama3_8b(message: str, history: list, temperature: float, max_new_tokens: int): | |
| conversation = [] | |
| for user, assistant in history: | |
| conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}]) | |
| conversation.append({"role": "user", "content": message}) | |
| input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt").to(model.device) | |
| streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True) | |
| generate_kwargs = dict( | |
| input_ids=input_ids, | |
| streamer=streamer, | |
| max_new_tokens=max_new_tokens, | |
| do_sample=True, | |
| temperature=temperature, | |
| eos_token_id=terminators, | |
| ) | |
| if temperature == 0: | |
| generate_kwargs['do_sample'] = False | |
| t = Thread(target=model.generate, kwargs=generate_kwargs) | |
| t.start() | |
| outputs = [] | |
| for text in streamer: | |
| outputs.append(text) | |
| yield "".join(outputs) | |
| # Gradio block | |
| chatbot = gr.Chatbot(height=450, placeholder=PLACEHOLDER, label='Gradio ChatInterface') | |
| with gr.Blocks(css=css) as demo: | |
| gr.Markdown(DESCRIPTION) | |
| gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button") | |
| gr.ChatInterface( | |
| fn=chat_llama3_8b, | |
| chatbot=chatbot, | |
| fill_height=True, | |
| additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False), | |
| additional_inputs=[ | |
| gr.Slider(minimum=0, | |
| maximum=1, | |
| step=0.1, | |
| value=0.95, | |
| label="Temperature", | |
| render=False), | |
| gr.Slider(minimum=128, | |
| maximum=4096, | |
| step=1, | |
| value=512, | |
| label="Max new tokens", | |
| render=False ), | |
| ], | |
| examples=[ | |
| ['What are the key differences between a sole proprietorship and a partnership?'], | |
| ['What legal steps should I take if I want to start a business in the US?'], | |
| ['Can you explain the concept of "duty of care" in negligence law?'], | |
| ['What are the legal requirements for obtaining a patent in Canada?'], | |
| ['How can I protect my intellectual property when sharing my idea with potential investors?'] | |
| ], | |
| cache_examples=False, | |
| ) | |
| gr.Markdown(LICENSE) | |
| if __name__ == "__main__": | |
| demo.launch(share=True) | |