| 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 = [ |
| ["🎸 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Everclear songs. 🎤"], |
| ["🎵 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Taylor Swift songs. 🎶"], |
| ["🎙️ Show full verse, chorus, intro, and outro chords and lyrics for top 3 Adele songs. 🎧"], |
| ["🎼 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Bruno Mars songs. 🎷"], |
| ["🎹 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Lady Gaga songs. 🎺"], |
| ["🎻 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Ed Sheeran songs. 🥁"], |
| ["🎤 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Drake songs. 🎶"], |
| ["🎧 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Rihanna songs. 🎵"], |
| ["🎷 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Justin Bieber songs. 🎼"], |
| ["🎶 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Beyoncé songs. 🎙️"], |
| ["🎺 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Katy Perry songs. 🎹"], |
| ["🥁 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Eminem songs. 🎻"], |
| ["🎤 Show full verse, chorus, intro, and outro chords and lyrics for top 3 Ariana Grande songs. 🎧"] |
| ] |
| ) |
| 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) |
| |
| |
| def SpeechSynthesis(result): |
| documentHTML5=''' |
| <!DOCTYPE html> |
| <html> |
| <head> |
| <title>Read It Aloud</title> |
| <script type="text/javascript"> |
| function readAloud() { |
| const text = document.getElementById("textArea").value; |
| const speech = new SpeechSynthesisUtterance(text); |
| window.speechSynthesis.speak(speech); |
| } |
| </script> |
| </head> |
| <body> |
| <h1>🔊 Read It Aloud</h1> |
| <textarea id="textArea" rows="10" cols="80"> |
| ''' |
| documentHTML5 = documentHTML5 + result |
| documentHTML5 = documentHTML5 + ''' |
| </textarea> |
| <br> |
| <button onclick="readAloud()">🔊 Read Aloud</button> |
| </body> |
| </html> |
| ''' |
| gr.HTML(documentHTML5) |
| |
| |
| SpeechSynthesis(markdown) |
| |
| |
| demo.queue().launch(debug=True) |
