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Local CLI Copilot, powered by Ollama. 💻🦙
An open-source implementaion for fine-tuning Qwen2-VL and Qwen2.5-VL series by Alibaba Cloud.
[EMNLP 2025] OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking
Experimental tools to backdoor large language models by re-writing their system prompts at a raw parameter level. This allows you to potentially execute offline remote code execution without running any actual code on the victim's machine or thwart LLM-based fraud/moderation systems.
GPU-accelerated Llama3.java inference in pure Java using TornadoVM.
A light llama-like llm inference framework based on the triton kernel.
Deploy open-source LLMs on AWS in minutes — with OpenAI-compatible APIs and a powerful CLI/SDK toolkit.
Hand-derived memory-efficient super lazy PyTorch VJPs for training LLMs on laptop, all using one op (bundled scaled matmuls).
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
Exploring Agno framework for building AI agents.
Community-built Qwen AI Provider for Vercel AI SDK - Integrate Alibaba Cloud's Qwen models with Vercel's AI application framework
Project Zephyrine: Your personal experimental glass cockpit for the world of ideas. Let's take flight with a modern, locally-run automaton, using accelerated thought to navigate the both digital aether and reality. skim the clouds of discovery.
Simple RAG system powered by Milvus.
Get Clothes from image
Silver Medal Solution for the Kaggle Competition: Eedi - Mining Misconceptions in Mathematics
Models: Deepseek R1 models, Llama3.2, Qwen2.5. Integrations: Ollama, Gradio. Supports Local LLM. Test and deploy the latest LLM models in the fastest and most efficient way
grpo to train long form QA and instructions with long-form reward model
FastLongSpeech is a novel framework designed to extend the capabilities of Large Speech-Language Models for efficient long-speech processing without necessitating dedicated long-speech training data.