Popular GitHub Repositories for Geoscience Lm

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

?丰富生态、?支持扩展、?多模态 - 大模型原生即时通信机器人平台 | 适配 QQ / 微信（企业微信、个人微信）/ 飞书 / 钉钉 / Discord / Telegram 等消息平台 | 支持 ChatGPT、DeepSeek、Dify、Claude、Gemini、xAI Grok、Ollama、LM Studio、阿里云百炼、火山方舟、SiliconFlow、Qwen、Moonshot、ChatGLM、SillyTraven 等 LLM 的机器人 / Agent | LLM-based instant messaging bots platform, supports Discord, Telegram, WeChat, Lark, DingTalk, QQ

Fengshenbang-LM(封神榜大模型)是IDEA研究院认知计算与自然语言研究中心主导的大模型开源体系，成为中文AIGC和认知智能的基础设施。

General technology for enabling AI capabilities w/ LLMs and MLLMs

Implementation for MatMul-free LM.

An unofficial PyTorch implementation of the audio LM VALL-E

A Node.js CLI that uses Ollama and LM Studio models (Llava, Gemma, Llama etc.) to intelligently rename files by their contents

LM Studio TypeScript SDK

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

A curated list of resources focused on Machine Learning in Geospatial Data Science.

Make Discord your LLM frontend ● Supports any OpenAI compatible API (Ollama, LM Studio, vLLM, OpenRouter, xAI, Mistral, Groq and more)

C++ implementation of Qwen-LM

LM Studio Python SDK

End-to-end ASR/LM implementation with PyTorch

Generate and brainstorm ideas while creating your notes using Large Language Models (LLMs) from Ollama, LM Studio, Anthropic, Google Gemini, Mistral AI, OpenAI, and more for Obsidian.

Personal Project: MPP-Qwen14B & MPP-Qwen-Next(Multimodal Pipeline Parallel based on Qwen-LM). Support [video/image/multi-image] {sft/conversations}. Don't let the poverty limit your imagination! Train your own 8B/14B LLaVA-training-like MLLM on RTX3090/4090 24GB.

Run Orpheus 3B Locally With LM Studio

Efficient visual programming for AI language models

?Language Model based sentences scoring library

Super-Efficient RLHF Training of LLMs with Parameter Reallocation