from huggingface_hub import InferenceClient import gradio as gr client = InferenceClient("""K00B404/BagOMistral_14X_Coders-ties-7B""")) def format_prompt(message, history, model): prompt = f"[INST] {message} [/INST]" for user_prompt, bot_response in history: prompt += f"[INST] {user_prompt} [/”" prompt += f" {bot_response} [/”" prompt = f"[MODEL] {model} [/”" + prompt return prompt def generate(prompt, history, temperature=0.2, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, model="BagOMistral_14X_Coders-ties-7B"): 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, model) 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) model_options = ["BagOMistral_14X_Coders-ties-7B", "Model2", "Model3", "Model4", "Model5", "Model6", "Model7"] demo = gr.ChatInterface(fn=generate, chatbot=mychatbot, title="K00B404's Merged Models Test Chat", retry_btn=None, undo_btn=None, inputs=["text", "history", "temperature", "max_new_tokens", "top_p", "repetition_penalty", "model"], inputs_types={"model": "dropdown", "text": "text", "history": "text", "temperature": "number", "max_new_tokens": "number", "top_p": "number", "repetition_penalty": "number"}, input_labels={"model": "Select Model", "text": "Enter Prompt", "history": "Chat History", "temperature": "Temperature", "max_new_tokens": "Max New Tokens", "top_p": "Top P", "repetition_penalty": "Repetition Penalty"}, input_options={"model": model_options}) demo.queue().launch(show_api=False)