TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #14788 · Jun 5

#cplusplus#avx#avx_512#avx_instructions#avx2#avx512#intrinsics#neon#simd#simd_instructions#simd_intrinsics#simd_library#simd_parallelism#simd_programming#sse42#wasm Highway is a C++ library that helps make software run faster and use less energy. It does this by using SIMD (Single Instruction, Multiple Data) instructions, which let the CPU perform the same operation on many pieces of data at once. This can make programs up to 10 times faster and reduce energy use by up to five times. Highway works on many different types of computers and is easy to use, making it a good choice for developers who want to improve their software's performance. https://github.com/google/highway

Results

2 similar posts found

Search: #llava

当前筛选 #llava清除筛选
Илья AGI TV 🤖

@ilia_plasma · Post #148 · 10/08/2023, 12:16 PM

Пока весь мир ждет доступа к новой модели со зрением GPT-4V(ision), опенсорс команда (пара азитов со степенью PhD из американских вузов) уже выпустили свой аналог и бесплатную версию #LLaVA (Large Language and Vision Assistant), которая выдает результат (не) хуже GPT4V и может работать локально. Вот такая скорость развития и конкуренции в этом новом #AI рынке. 🧠LLava - вебсайт 📄WhitePaper 🧬Github code 🔋Demo для потестить на своих дикпиках 🦒Colab (для запуска у себя на серваке)

Hashtags

GitHub Trends

@githubtrending · Post #15600 · 04/04/2026, 11:30 AM

#python#apple_silicon#florence2#idefics#llava#llm#local_ai#mlx#molmo#paligemma#pixtral#vision_framework#vision_language_model#vision_transformer MLX-VLM lets you run, chat with, and fine-tune Vision Language Models (VLMs) plus audio/video models on your Mac using MLX—install easily with `pip install -U mlx-vlm`. Use CLI for quick text/image/audio generation (e.g., `mlx_vlm.generate --model ... --image photo.jpg`), Gradio UI for chats, Python scripts, or a FastAPI server with OpenAI-compatible endpoints supporting multi-images/videos. Features like TurboQuant cut KV cache memory by 76%, and LoRA/QLoRA fine-tuning works on consumer hardware. You benefit by experimenting with powerful multimodal AI locally—fast, memory-efficient, no cloud costs, perfect for Mac users tweaking models affordably. https://github.com/Blaizzy/mlx-vlm