Build your nutritional plan using AI
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Updated
Jun 2, 2024 - Python
Build your nutritional plan using AI
Python Co-Pilot enhances Python developers' coding experience by utilizing LLama's advanced language understanding and Mistral's intelligent code generation, enabling more efficient and high-quality code writing.
Evaluate LLMs capability of assessing semantic relations
In this repository I explore the Idea of a concept search in text. Instead of using full text search or serching for exact strings I search for concepts in the text. Specifically I search for the concept of seeking discomfort in the book Matthew in the bible.
RAG (Retrieval Augmented Generation) and vector search to translate natural language into SQL queries for PostgreSQL databases.
Simple Question Answering using TheBloke/Mistral-7B-Instruct-v0.1-GGUF. Deployed on HuggingFace Space.
CodeStral-Code-Assistant is a chatbot designed to assist users with code-related questions. It provides code solutions, including descriptions, programming language details, imports, functional code blocks, and sample input/output.
A Simple To Use Mistral AI Client
A versatile CLI and Python wrapper for Mistral AI's 'Mixtral' and 'Mistral' large language models. Streamline the creation of chatbots and generate dynamic text with ease.
TDMRep: TDM Reservation Protocol integration for WordPress
Choose the model that's right for you
A place to evaluate public models
Sentiment Analysis of customer reviews for Airlines using RoBERTa and BART and then use LDA to identify themes. Use LLM to create an industry analysis report identifying opportunities for disruption and innovation. Based on data set (kaggle datasets download -d juhibhojani/airline-reviews) from Kaggle.
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