Popular GitHub Repositories for Codellama

A self-hosted, offline, ChatGPT-like chatbot. Powered by Llama 2. 100% private, with no data leaving your device. New: Code Llama support!

LMDeploy is a toolkit for compressing, deploying, and serving LLMs.

Create chatbots with ease

The leading open-source AI copilot for JetBrains. Connect to any model in any environment, and customize your coding experience in any way you like.

An open-source alternative to GitHub copilot that runs locally.

Make Llama2 use Code Execution, Debug, Save Code, Reuse it, Access to Internet

Use Code Llama with Visual Studio Code and the Continue extension. A local LLM alternative to GitHub Copilot.

Local first semantic code search and chat | Leverage custom copilots with fine-tuning datasets from code in Alpaca, Conversational, Completion and Instruction format

An AI code interpreter for sensitive data, powered by GPT-4 or Code Llama / Llama 2.

Loz is a command-line tool that enables your preferred LLM to execute system commands and utilize Unix pipes, integrating AI capabilities with other Unix tools.

Open source chat kit engineered for seamless interaction with AI models.

Deploy a RESTful API Server to interact with Ollama and Stable Diffusion

Benchmark your local LLMs.

RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair http://arxiv.org/pdf/2312.15698

Codellama Instruct OpenAi style api.

codellama on CPU without Docker

Use ollama llms for code completion

SHUKUN AI is an AI-native database search application that helps companies explore and analyze data. SHUKUN AI provides a feature that helps you split complex natural language tasks into smaller parts then combines them into the results.

Run a local instance of a code-specialized model via Ollama using docker compose and connect to your VSCode for code completion / generation.

Prompt engineering with Langchain and fine-tuning the CodeLlama model. The main aim is to generate task-specific C++ code snippets. Experiment with various prompts and models to create accurate C++ code. Unit test is conducted to validate the correctness and effectiveness of the generated code snippets.