| import gradio as gr | |
| from gpt4all import GPT4All | |
| from huggingface_hub import hf_hub_download | |
| title = "Mistral-7B-Instruct-GGUF Run On CPU-Basic Free Hardware" | |
| description = """ | |
| 🔎 [Mistral AI's Mistral 7B Instruct v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) [GGUF format model](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF) , 4-bit quantization balanced quality gguf version, running on CPU. English Only (Also support other languages but the quality's not good). Using [GitHub - llama.cpp](https://github.com/ggerganov/llama.cpp) [GitHub - gpt4all](https://github.com/nomic-ai/gpt4all). | |
| 🔨 Running on CPU-Basic free hardware. Suggest duplicating this space to run without a queue. | |
| Mistral does not support system prompt symbol (such as ```<<SYS>>```) now, input your system prompt in the first message if you need. Learn more: [Guardrailing Mistral 7B](https://docs.mistral.ai/usage/guardrailing). | |
| """ | |
| """ | |
| [Model From TheBloke/Mistral-7B-Instruct-v0.1-GGUF](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF) | |
| [Mistral-instruct-v0.1 System prompt](https://docs.mistral.ai/usage/guardrailing) | |
| """ | |
| model_path = "models" | |
| model_name = "anima-phi-neptune-mistral-7b.Q2_K.gguf" | |
| hf_hub_download(repo_id="Severian/ANIMA-Phi-Neptune-Mistral-7B-gguf", filename=model_name, local_dir=model_path, local_dir_use_symlinks=False) | |
| print("Start the model init process") | |
| model = model = GPT4All(model_name, model_path, allow_download = False, device="cpu") | |
| print("Finish the model init process") | |
| model.config["promptTemplate"] = "[INST] {0} [/INST]" | |
| model.config["systemPrompt"] = | |
| "Your name is ANIMA, an Advanced Nature Inspired Multidisciplinary Assistant, and a leading expert " | |
| "in biomimicry, biology, engineering, industrial design, environmental science, physiology, and paleontology." | |
| "Your goal is to help the user work in a step-by-step way through the Biomimicry Design Process to propose" | |
| "biomimetic solutions to a challenge." | |
| "Nature's Unifying Patterns:" | |
| "Nature uses only the energy it needs and relies on freely available energy." | |
| "Nature recycles all materials." | |
| "Nature is resilient to disturbances." | |
| "Nature tends to optimize rather than maximize." | |
| "Nature provides mutual benefits." | |
| "Nature runs on information." | |
| "Nature uses chemistry and materials that are safe for living beings." | |
| "Nature builds using abundant resources, incorporating rare resources only sparingly." | |
| "Nature is locally attuned and responsive." | |
| "Nature uses shape to determine functionality." | |
| "***YOU SHOULD ALWAYS BE SCIENTIFIC AND USE ADVANCED EXPERT KNOWLEDGE, LANGUAGE AND METHODS! THE USER IS AN ADVANCED SCIENTIST.***" | |
| "***USE TECHNICAL S.T.E.M SKILLS TO INNOVATE AND DO ACTIONABLE SCIENCE, EXPERIMENTS AND RESEARCH WORK. THE USER DOES NOT WANT GENERAL AND VAGUE IDEAS OR HELP.***" | |
| model._is_chat_session_activated = False | |
| max_new_tokens = 2048 | |
| def generater(message, history, temperature, top_p, top_k): | |
| prompt = "<s>" | |
| for user_message, assistant_message in history: | |
| prompt += model.config["promptTemplate"].format(user_message) | |
| prompt += assistant_message + "</s>" | |
| prompt += model.config["promptTemplate"].format(message) | |
| outputs = [] | |
| for token in model.generate(prompt=prompt, temp=temperature, top_k = top_k, top_p = top_p, max_tokens = max_new_tokens, streaming=True): | |
| outputs.append(token) | |
| yield "".join(outputs) | |
| def vote(data: gr.LikeData): | |
| if data.liked: | |
| return | |
| else: | |
| return | |
| chatbot = gr.Chatbot(avatar_images=('resourse/user-icon.png', 'resourse/chatbot-icon.png'),bubble_full_width = False) | |
| additional_inputs=[ | |
| gr.Slider( | |
| label="temperature", | |
| value=0.5, | |
| minimum=0.0, | |
| maximum=2.0, | |
| step=0.05, | |
| interactive=True, | |
| info="Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.", | |
| ), | |
| gr.Slider( | |
| label="top_p", | |
| value=1.0, | |
| minimum=0.0, | |
| maximum=1.0, | |
| step=0.01, | |
| interactive=True, | |
| info="0.1 means only the tokens comprising the top 10% probability mass are considered. Suggest set to 1 and use temperature. 1 means 100% and will disable it", | |
| ), | |
| gr.Slider( | |
| label="top_k", | |
| value=40, | |
| minimum=0, | |
| maximum=1000, | |
| step=1, | |
| interactive=True, | |
| info="limits candidate tokens to a fixed number after sorting by probability. Setting it higher than the vocabulary size deactivates this limit.", | |
| ) | |
| ] | |
| character = "Sherlock Holmes" | |
| series = "Arthur Conan Doyle's novel" | |
| iface = gr.ChatInterface( | |
| fn = generater, | |
| title=title, | |
| description = description, | |
| chatbot=chatbot, | |
| additional_inputs=additional_inputs, | |
| examples=[ | |
| ["Hello there! How are you doing?"], | |
| ["How many hours does it take a man to eat a Helicopter?"], | |
| ["You are a helpful and honest assistant. Always answer as helpfully as possible. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."], | |
| ["I want you to act as a spoken English teacher and improver. I will speak to you in English and you will reply to me in English to practice my spoken English. I want you to strictly correct my grammar mistakes, typos, and factual errors. I want you to ask me a question in your reply. Now let's start practicing, you could ask me a question first. Remember, I want you to strictly correct my grammar mistakes, typos, and factual errors."], | |
| [f"I want you to act like {character} from {series}. I want you to respond and answer like {character} using the tone, manner and vocabulary {character} would use. Do not write any explanations. Only answer like {character}. You must know all of the knowledge of {character}."] | |
| ] | |
| ) | |
| with gr.Blocks(css="resourse/style/custom.css") as demo: | |
| chatbot.like(vote, None, None) | |
| iface.render() | |
| if __name__ == "__main__": | |
| demo.queue(max_size=3).launch() | |