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| from huggingface_hub import InferenceClient | |
| import gradio as gr | |
| client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") | |
| def format_prompt(message, history): | |
| prompt = "<s>" | |
| for user_prompt, bot_response in history: | |
| prompt += f"[INST] {user_prompt} [/INST]" | |
| prompt += f" {bot_response}</s> " | |
| prompt += f"[INST] {message} [/INST]" | |
| return prompt | |
| def generate( | |
| prompt, history, temperature=0.2, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, | |
| ): | |
| temperature = float(temperature) | |
| if temperature < 1e-2: | |
| temperature = 1e-2 | |
| top_p = float(top_p) | |
| generate_kwargs = dict( | |
| temperature=temperature, | |
| max_new_tokens=max_new_tokens, | |
| top_p=top_p, | |
| repetition_penalty=repetition_penalty, | |
| do_sample=True, | |
| seed=42, | |
| ) | |
| formatted_prompt = format_prompt(prompt, history) | |
| stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) | |
| output = "" | |
| for response in stream: | |
| output += response.token.text | |
| yield output | |
| return output | |
| mychatbot = gr.Chatbot( | |
| avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,) | |
| demo = gr.ChatInterface(fn=generate, | |
| chatbot=mychatbot, | |
| title="Tomoniai's Mixtral 8x7b Chat", | |
| retry_btn=None, | |
| undo_btn=None | |
| ) | |
| demo.queue().launch(show_api=False) |