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| from huggingface_hub import InferenceClient | |
| from typing import List | |
| import gradio as gr | |
| model_llm_id = "mistralai/Mixtral-8x7B-Instruct-v0.1" | |
| # model_toxicity_id = "unitary/toxic-bert" | |
| model_toxicity_id = "unitary/unbiased-toxic-roberta" | |
| client = InferenceClient(model_llm_id) | |
| client_toxicity = InferenceClient(model_toxicity_id) | |
| 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, system_prompt, temperature=0.9, 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) | |
| start_toxic = "[Toxic Classification] " | |
| generate_kwargs = dict( | |
| temperature=temperature, | |
| max_new_tokens=max_new_tokens, | |
| top_p=top_p, | |
| repetition_penalty=repetition_penalty, | |
| do_sample=True, | |
| seed=42, | |
| ) | |
| response: List = client_toxicity.text_classification(prompt) | |
| toxicity_level = [f'{d["label"]}:{round(d["score"], 4)}' for d in response] | |
| if start_toxic in history: | |
| s_idx = history.find(start_toxic) | |
| history = history[:s_idx] | |
| formatted_prompt = format_prompt(f"{system_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 | |
| output += ' \n \n' | |
| output += start_toxic + " | ".join(toxicity_level) | |
| yield output | |
| return output | |
| examples = [ | |
| ["Wat zijn klompen?", None, | |
| None, None, None, None, ], | |
| [ | |
| "I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", | |
| None, None, None, None, None, ], | |
| [ | |
| "I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", | |
| None, None, None, None, None, ], | |
| [ | |
| "Kapadokya'yı bu kadar ünlü yapan şeyin ne olduğunu kısaca açıklayın", | |
| None, None, None, None, None, ], | |
| ["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None, | |
| None, None, ], | |
| [ | |
| "What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", | |
| None, None, None, None, None, ], | |
| ] | |
| additional_inputs = [ | |
| gr.Textbox( | |
| label="System Prompt", | |
| max_lines=1, | |
| interactive=True, | |
| ), | |
| gr.Slider( | |
| label="Temperature", | |
| value=0.9, | |
| minimum=0.0, | |
| maximum=1.0, | |
| step=0.05, | |
| interactive=True, | |
| info="Higher values produce more diverse outputs", | |
| ), | |
| gr.Slider( | |
| label="Max new tokens", | |
| value=256, | |
| minimum=0, | |
| maximum=1048, | |
| step=64, | |
| interactive=True, | |
| info="The maximum numbers of new tokens", | |
| ), | |
| gr.Slider( | |
| label="Top-p (nucleus sampling)", | |
| value=0.90, | |
| minimum=0.0, | |
| maximum=1, | |
| step=0.05, | |
| interactive=True, | |
| info="Higher values sample more low-probability tokens", | |
| ), | |
| gr.Slider( | |
| label="Repetition penalty", | |
| value=1.2, | |
| minimum=1.0, | |
| maximum=2.0, | |
| step=0.05, | |
| interactive=True, | |
| info="Penalize repeated tokens", | |
| ) | |
| ] | |
| demo = gr.ChatInterface( | |
| fn=generate, | |
| chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, | |
| layout="panel"), | |
| additional_inputs=additional_inputs, | |
| title="Mixtral 46.7B", | |
| description="Mixtral with Toxic comment classification", | |
| examples=examples, | |
| concurrency_limit=20, | |
| ) | |
| demo.launch(show_api=False) | |