An open-source implementaion for fine-tuning Qwen-VL series by Alibaba Cloud.
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Updated
Apr 10, 2026 - Python
An open-source implementaion for fine-tuning Qwen-VL series by Alibaba Cloud.
Run generative AI models in sophgo BM1684X/BM1688
A privacy-first Android chat app that runs large language models entirely on-device. No internet, no cloud, no tracking. Built with Kotlin, Jetpack Compose, and llama.cpp with optimized ARM NEON/SVE inference.
Make Local AI Toys, Robots, Devices that with a MacBook and an Arduino ESP32
MCore-Bridge: Providing Megatron-Core model definitions for state-of-the-art large models and making Megatron training as simple as Transformers — with support for 300+ large language models (Qwen3-Next, GLM-5.1, Deepseek-V3.2, MiniMax-2.7, ...) and 200+ multimodal large models (Qwen3.5, Qwen3-Omni, Gemma4, ...).
4-5x faster Qwen3.5 on ASUS GX10 / DGX Spark — Hybrid INT4+FP8 + MTP via one shell script
PulseCoreLite is a desktop performance monitoring application based on Tauri 2 and Vue 3. It offers two forms of monitoring: floating window monitoring and taskbar monitoring. It displays real-time indicators such as CPU, GPU, memory, disk, and network, and supports system-level capabilities such as multiple languages, transparency and refresh rate
7.67× LoRA / 8.35× Full FT speedup for Qwen3.5 (0.8B–27B) on NVIDIA DGX Spark — wall-clock parity with rented H100. Lossless within BF16. Three-command interactive wizard handles model picker, data validator, training, and merge.
Fast Qwen 3.5 inference in pure Java
Adaptive routing system combining YOLOv8s and Qwen3.5-0.8B VLM for semantic disambiguation of low-confidence detections on VOC2012.
Qwen 3.5 Reverse Proxy for handling instant / thinking modes and their variants automatically
SAM3-Plus-Qwen3.5 is an advanced, experimental computer vision suite that seamlessly integrates Facebook's Segment Anything Model 3 (SAM3) with the Qwen3.5 multimodal reasoning engine.
Demo application provides an interactive Gradio-based interface for exploring the multimodal capabilities of the Qwen/Qwen3.5-2B model from Hugging Face. Built with a focus on accessibility and real-time interaction, it enables users to perform a variety of vision-language tasks.
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