Interact with your PDF documents like never before! ๐คฏ Extract text & images, then ask context-aware questions based on both. Powered by RAG techniques & multimodal LLMs. Perfect for studying, research & more! ๐๐ Try it out now!!!! โ๏ธ
Just launched the zamal/DeepSeek-VL-1.3B-Chat on Hugging Face, and it's ready for YOU to explore! ๐ฌ๐ผ๏ธ
This full-fledged model is perfect for advanced image and text interactions, with zero GPU required. The Deepseek VL-1.3B Chat typically needs around 8 GB of VRAM and storage of almost 4 GB, but now you can experience it hassle-free right on our space!
Want something lighter? Weโve also uploaded a 4 bit quantized version (just around 1GB!), available on my profile. Perfect for those with limited hardware. ๐๐
Come try it now and see what this model can do! ๐โจ
Just launched the zamal/DeepSeek-VL-1.3B-Chat on Hugging Face, and it's ready for YOU to explore! ๐ฌ๐ผ๏ธ
This full-fledged model is perfect for advanced image and text interactions, with zero GPU required. The Deepseek VL-1.3B Chat typically needs around 8 GB of VRAM and storage of almost 4 GB, but now you can experience it hassle-free right on our space!
Want something lighter? Weโve also uploaded a 4 bit quantized version (just around 1GB!), available on my profile. Perfect for those with limited hardware. ๐๐
Come try it now and see what this model can do! ๐โจ
zamal/Molmo-4bit Thrilled to announce that the Molmo 7B 4-bit Space is now live! ๐ The model size has been reduced by six times with almost no performance loss, and the results will leave you amazed!
It runs on zero GPU, making it incredibly accessible for everyone!
zamal/Molmo-4bit Thrilled to announce that the Molmo 7B 4-bit Space is now live! ๐ The model size has been reduced by six times with almost no performance loss, and the results will leave you amazed!
It runs on zero GPU, making it incredibly accessible for everyone!
๐ New Model Release: zamal/Molmo-7B-GPTQ-4bit ๐
Hello lovely community,
zamal/Molmo-7B-GPTQ-4bit model is now available for all! This model has been highly quantized, reducing its size by almost six times. It now occupies significantly less space and vRAM, making it perfect for deployment on resource-constrained devices without compromising performance.
Now we get: Efficient Performance: Maintains high accuracy while being highly quantized. Reduced Size: The model size is reduced by nearly six times, optimizing storage and memory usage. Versatile Application: Ideal for integrating a powerful visual language model into various projects particularly multi rag chains. Check it out!