| from huggingface_hub import InferenceClient | |
| import gradio as gr | |
| client = InferenceClient( | |
| "mistralai/Mistral-7B-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=0.9, 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) | |
| 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 | |
| additional_inputs=[ | |
| 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", | |
| ) | |
| ] | |
| css = """ | |
| #mkd { | |
| height: 200px; | |
| overflow: auto; | |
| border: 1px solid #ccc; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| gr.ChatInterface( | |
| generate, | |
| additional_inputs=additional_inputs, | |
| examples = [ | |
| ["🏰 Welcome to the Kingdom of Elandria! You are Jim and Tim, two bumbling bros with a knack for mischief. 🤴🤴 [Action: Introduce yourselves, Equipment: Scepters of Foolishness]"], | |
| ["🌲 You find yourselves in a forest filled with magical creatures and oddly specific 'Do Not Disturb' signs. 🦄 [Action: Proceed cautiously, Equipment: Map of Social Etiquette]"], | |
| ["🍻 You stumble upon a dwarf tavern. They offer you 'Beard Beer.' Do you drink it? 🍺 [Action: Chug or Pass, Equipment: Empty Mugs]"], | |
| ["🐉 A vegan dragon appears and chastises you for your leather boots. What do you do? 🗡️🏃 [Action: Apologize and offer kale, Equipment: Non-leather sandals]"], | |
| ["💎 You find a treasure chest labeled 'Not a Mimic.' Seems legit. Do you open it? 🗝️ [Action: Open or No way, Equipment: Mimic Repellent]"], | |
| ["🦇 You're swarmed by bats in a cave. One bat offers you 'organic guano.' How do you react? 🕯️ [Action: Politely decline, Equipment: Nose Plugs]"], | |
| ["🔮 A mysterious sorcerer offers you a 'Love Potion No. 9½.' Do you take a sip? 🍶 [Action: Sip or Skip, Equipment: Breath Mints]"], | |
| ["⚔️ Bandits demand gold, but they accept credit cards. What's your move? 💰 [Action: Pay or Pray, Equipment: Wallets]"], | |
| ["🚪 A door with three locks and a sign saying 'Beware of the Dog.' Do you search for the keys or try to pet the dog? 🗝️💪 [Action: Unlock or Pet, Equipment: Dog Treats]"], | |
| ["🌊 A river blocks your path. A mermaid offers to carry you across for a 'small' fee. 🏊♀️🌉 [Action: Accept or Decline, Equipment: Bargaining Skills]"], | |
| ["🦁 You encounter a pride of lions playing poker. Do you join the game or fold? 🤫🔄 [Action: Play or Fold, Equipment: Poker Face]"], | |
| ["🍎 A tree filled with golden apples and a sign saying, 'Seriously, don't eat these!' What do you do? 🤔 [Action: Eat or Retreat, Equipment: Stomach Pump]"], | |
| ["🌕 The moon turns red, wolves start howling, and your horoscope says 'Stay in bed.' Do you camp or go? 🏕️🚶 [Action: Camp or Scamp, Equipment: Astrology App]"], | |
| ["💀 The final boss is an undead warrior selling life insurance. Do you combat or sign up? ⚔️🤝 [Action: Fight or Finance, Equipment: Policy Guide]"] | |
| ] | |
| ) | |
| gr.HTML("""<h2>🤖 Mistral Chat - Gradio 🤖</h2> | |
| In this demo, you can chat with <a href='https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1'>Mistral-7B-Instruct</a> model. 💬 | |
| Learn more about the model <a href='https://huggingface.co/docs/transformers/main/model_doc/mistral'>here</a>. 📚 | |
| <h2>🛠 Model Features 🛠</h2> | |
| <ul> | |
| <li>🪟 Sliding Window Attention with 128K tokens span</li> | |
| <li>🚀 GQA for faster inference</li> | |
| <li>📝 Byte-fallback BPE tokenizer</li> | |
| </ul> | |
| <h3>📜 License 📜 Released under Apache 2.0 License</h3> | |
| <h3>📦 Usage 📦</h3> | |
| <ul> | |
| <li>📚 Available on Huggingface Hub</li> | |
| <li>🐍 Python code snippets for easy setup</li> | |
| <li>📈 Expected speedups with Flash Attention 2</li> | |
| </ul> | |
| """) | |
| markdown=""" | |
| | Feature | Description | Byline | | |
| |---------|-------------|--------| | |
| | 🪟 Sliding Window Attention with 128K tokens span | Enables the model to have a larger context for each token. | Increases model's understanding of context, resulting in more coherent and contextually relevant outputs. | | |
| | 🚀 GQA for faster inference | Graph Query Attention allows faster computation during inference. | Speeds up the model inference time without sacrificing too much on accuracy. | | |
| | 📝 Byte-fallback BPE tokenizer | Uses Byte Pair Encoding but can fall back to byte-level encoding. | Allows the tokenizer to handle a wider variety of input text while keeping token size manageable. | | |
| | 📜 License | Released under Apache 2.0 License | Gives you a permissive free software license, allowing you freedom to use, modify, and distribute the code. | | |
| | 📦 Usage | | | | |
| | 📚 Available on Huggingface Hub | The model can be easily downloaded and set up from Huggingface. | Makes it easier to integrate the model into various projects. | | |
| | 🐍 Python code snippets for easy setup | Provides Python code snippets for quick and easy model setup. | Facilitates rapid development and deployment, especially useful for prototyping. | | |
| | 📈 Expected speedups with Flash Attention 2 | Upcoming update expected to bring speed improvements. | Keep an eye out for this update to benefit from performance gains. | | |
| # 🛠 Model Features and More 🛠 | |
| ## Features | |
| - 🪟 Sliding Window Attention with 128K tokens span | |
| - **Byline**: Increases model's understanding of context, resulting in more coherent and contextually relevant outputs. | |
| - 🚀 GQA for faster inference | |
| - **Byline**: Speeds up the model inference time without sacrificing too much on accuracy. | |
| - 📝 Byte-fallback BPE tokenizer | |
| - **Byline**: Allows the tokenizer to handle a wider variety of input text while keeping token size manageable. | |
| - 📜 License: Released under Apache 2.0 License | |
| - **Byline**: Gives you a permissive free software license, allowing you freedom to use, modify, and distribute the code. | |
| ## Usage 📦 | |
| - 📚 Available on Huggingface Hub | |
| - **Byline**: Makes it easier to integrate the model into various projects. | |
| - 🐍 Python code snippets for easy setup | |
| - **Byline**: Facilitates rapid development and deployment, especially useful for prototyping. | |
| - 📈 Expected speedups with Flash Attention 2 | |
| - **Byline**: Keep an eye out for this update to benefit from performance gains. | |
| """ | |
| gr.Markdown(markdown) | |
| demo.queue().launch(debug=True) |