#Mistral-7b
Showing 20 of 20 repositories tagged #mistral-7b, ranked by stars
Fully-featured web interface for Ollama LLMs
Chat with your documents using local AI
turnkey self-hosted offline transcription and diarization service with llm summary
LLM (Large Language Model) FineTuning
AubAI brings you on-device gen-AI capabilities, including offline text generation and more, directly within your app.
Build LLM-powered robots in your garage with MachinaScript For Robots!
Run AI workloads easily in a decentralized GPU network. https://www.youtube.com/watch?v=yQnB2Yxia4Y
VerifAI initiative to build open-source easy-to-deploy generative question-answering engine that can reference and verify answers for correctness (using posteriori model)
Querypls🛠️: WebApp that Simplify SQL with Your Prompts. Transforming questions into SQL commands effortlessly.
Small and Efficient Mathematical Reasoning LLMs
Chat With RTX Python API
Pull high-quality, efficient embeddings for PubMed, arXiv and Wikipedia from Huggingface and use for local LLM inference/Retrieval Augmented Generation (RAG)
Streamlit + Langchain + LlamaCPP + Mistral + Rag
Java 23, SpringBoot 3.4.1 Examples using Deep Learning 4 Java & LangChain4J for Generative AI using ChatGPT LLM, RAG and other open source LLMs. Sentiment Analysis, Application Context based ChatBots. Custom Data Handling. LLMs - GPT 3.5 / 4o, Gemini Pro 1.5, Claude 3, Llama 3.1, Phi-3, Gemma 2, Falcon 3, Qwen 2.5, Mistral Nemo, Wizard Math
Examples of RAG using LangChain with local LLMs - Mixtral 8x7B, Llama 2, Mistral 7B, Orca 2, Phi-2, Neural 7B
A Gradio web UI for Large Language Models. Supports LoRA/QLoRA finetuning,RAG(Retrieval-augmented generation) and Chat
A character chat with integrated medium and long-term memory
The AI-Powered Healthcare Intelligence Network is an AI-driven system offering disease prediction, drug recommendations, heart disease risk assessment, and an AI medical chatbot. Using ML, NLP, and LLMs, it provides accurate diagnoses, insights, and recommendations, enhancing healthcare accessibility, efficiency, and decision-making .
Taxonomy Completion with Embedding Quantization and an LLM-based Pipeline: A Case Study in Computational Linguistics
Helm Charts to deploy and manage OpenLIT in Kubernetes