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zamal 
posted an update 3 days ago
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310
🚀 Try Out RAG Demo! 🚀

A Hugging Face Space where you can compare DeepSeek-R1 vs Llama-3 using Stuff RAG (Retrieval-Augmented Generation)!

🔍 Upload a PDF, ask questions, and see how both models perform in real-time!

Try out now:
zamal/Deepseek-R1-vs-LLama3
  • 1 reply
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zamal 
posted an update 17 days ago
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1355
zamal/Multimodal-Chat-PDF

🚀 Introducing Chat PDF Multimodal 💬

Interact with your PDF documents like never before! 🤯
Extract text & images, then ask context-aware questions based on both. Powered by RAG techniques & multimodal LLMs. Perfect for studying, research & more! 📝👀
Try it out now!!!! ✍️

#LlavaNext #MultimodalAI #Transformers
zamal 
posted an update 4 months ago
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🚀 Announcement for the Lovely community! 🚀

Just launched the zamal/DeepSeek-VL-1.3B-Chat on Hugging Face, and it's ready for YOU to explore! 💬🖼️

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? We’ve also uploaded a 4 bit quantized version (just around 1GB!), available on my profile. Perfect for those with limited hardware. 🌍🔍

Come try it now and see what this model can do! 🚀✨
zamal 
posted an update 4 months ago
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2081
Hello, lovely community! 🌟

zamal/Molmo-4bit Thrilled to announce that the Molmo 7B 4-bit Space is now live! 🚀 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!

Check it out here and start exploring today!

Happy experimenting! 🎉
zamal 
posted an update 4 months ago
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1953
🚀 New Model Release: zamal/Molmo-7B-GPTQ-4bit 🚀

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!

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meyerls 
authored a paper 6 months ago
zamal 
posted an update 9 months ago
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1326
Finally!
My first post for the lovely community out there!

Here's a highly quantized finetuned version of gemma focused exclusively on Prompt Engineering. Write as ambiguous you want and leave the job to this model

zamal/gemma-7b-finetuned
Bibidibabidi 
updated a Space about 1 year ago