Nexa AI

We just reached 4,000 stars on GitHub! ? ?? A huge thanks to our amazing community—your support means the world. Let's keep pushing the boundaries of on-device AI! ?? Run GGUF & ONNX models, convert HuggingFace to GGUF, and evaluate models—all with Nexa SDK: github.com/NexaAI/nexa-sdk. Like what we’re building? Give us a star and share your feedback! ??

? Model Update: New GGUF File Live! The latest GGUF file for our improved OmniVision-968M is now available at our Hugging Face repo: https://lnkd.in/gPA-KHJi Thank you for all your valuable feedback that helped shape these updates! More exciting improvements are in development - stay tuned! Love what we're doing? Give us a like to show your support! ??

We’ve just improved OmniVision-968M based on your feedback! ?? The latest updates are now live as a preview in our Hugging Face Space powered by Gradio: https://lnkd.in/gk8AuQy9 Here’s what’s improved: 1?? Art Descriptions 2?? Complex Images 3?? Anime 4?? Color and Detail Recognition 5?? World Knowledge And there’s more to come! ?? This is just a preview—updated model files will be released in Hugging Face Repo after final alignment tweaks (Stay tuned for updates): https://lnkd.in/gmzaG_DE ?? We’re committed to continuously improve our model. Share your feedback in the comments, on Discord, or GitHub—we’d love to advance on-device multimodality (VLM) with your support! ?? A heartfelt thanks to everyone who contributed. Special thanks to community members: u/daaain, u/ransuko, u/nikkisNM, u/animemosquito from Reddit.

Experience OmniVision, our sub-billion-parameter multimodal model, delivering seamless AI capabilities on AMD-powered devices! Running on the AMDRyzen AI 9 HX 370, OmniVision showcases: ? Tiny Model Size: only 968M parameters ? Efficient Processing: Powered by AMD iGPU acceleration and Nexa AI collaborating with AMD on an NPU solution ? Developer-Ready: Full Nexa SDK support for AMD GPUs (ROCm & Vulkan, and NPU acceleration coming soon) On-device multimodal AI unlocks powerful daily applications: ?? Analyze and retrieve images to assist memory ?? Precisely describe food images ?? Quickly identify HDMI port locations ?? Full Blog on OmniVision: nexa.ai/blogs/omni-vision ?? Try the model on Hugging Face: https://lnkd.in/gmzaG_DE A huge thanks to AMD for their hardware innovation, enabling us to redefine what’s possible in multimodal AI—locally, on-device!

?? Meet OmniVision, a compact, sub-billion (968M) multimodal model optimized for edge devices. Improved on LLaVA's architecture, it processes both visual and text inputs with high efficiency for Visual Question Answering ?? and Image Captioning ???: - 9x Tokens Reduction: Reduces image tokens from 729 to 81, cutting latency and computational cost. - Trustworthy Result: Reduces hallucinations using DPO training from trustworthy data. ?? Try it out: https://lnkd.in/gk8AuQy9 ?? Like and Download OmniVision on Hugging Face: https://lnkd.in/gmzaG_DE Or ?? Run locally with Nexa SDK: - Install Nexa SDK https://lnkd.in/gXnBQ97D - Run on terminal: nexa run omnivision ?? Full blog: nexa.ai/blogs/omni-vision ?? Video Demo: Generating captions for a 1046×1568 pixel poster on M4 Pro Macbook takes <2s processing time and requires only 988 MB RAM and 948 MB Storage.

We are thrilled to announce that Nexa AI’s GitHub repo has reached 3000 stars!? ? ? This is a huge milestone for us, and we’re incredibly grateful to our amazing community of developers and supporters. ?? Big updates are coming soon ?? ?? —make sure to star our GitHub and stay in the loop: github.com/NexaAI/nexa-sdk. Your feedback, requests, and contributions are always welcome! ?? ?? Check out some well-loved features and example projects we released earlier: - Executables for easier model setup - Evaluation tools integrated with the SDK - Support for popular models, including models from Hugging Face - Streamlit support for better visualization ?? https://lnkd.in/gm69DCyG ?? Project Examples: - Chat with Local PDF: https://lnkd.in/g7qyUeCb - Local File Organization: https://lnkd.in/gKG5F7fE ?? Small Language Model Leaderboard: nexa.ai/leaderboard

?? Excited to announce our partnership with PIN AI to bring Nexa’s on-device AI models and local inference framework to mobile! PIN AI is building a visionary personal AI OS for mobile, enabling a powerful, private, and responsive AI experience right in the palm of your hand. This partnership is a leap toward a future where personal AI on mobile is secure, fast, and easily accessible. Stay tuned! ?? https://lnkd.in/d7SaRaPd

?? We just launched an On-Device Small Language Model (SLM) Leaderboard for all you local LLM fans! ?? Compare quantized versions of popular models like Llama3.2, Qwen2.5, Phi-3.5 based on quality (ifEval) and performance (response time, output speed, prefill speed, and power consumption). ?? Check it out & contribute: nexa.ai/leaderboard Want a specific model added? Join our Discord Server at https://lnkd.in/dUMJAXCU or submit a GitHub issue at github.com/NexaAI/nexa-sdk! ???

Thank you, Howie Xu, for hosting such a great discussion! Exciting things are on the way—we’re gearing up to release a series of multimodal models, and Nexa SDK will see major updates soon! Follow us at https://nexa.ai to stay updated on our journey in on-device AI!

?? Day 2 at TechCrunch Disrupt 2024 was on fire! We showcased our fresh Octopus on iOS demo, and the energy here has been incredible. ??? Don’t miss our pitch today at the SaaS, Enterprise + Productivity Stage. We can’t wait to share our vision for the future of on-device AI with you! ?? There’s still time to swing by Nexa AI's booth at L8 for more demos—snap a photo and tag us! ? Follow our GitHub repo and give us a star to be among the first to try Local AI on your mobile: github.com/NexaAI/nexa-sdk. Stay tuned, exciting things are on the way! ?? #TechCrunchDisrupt2024 #NexaAI #OnDeviceAI #LocalAI #SaaS #EnterpriseAI