SFEvent (Open-Source AI Meetup)

zamal

posted an update 8 days ago

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1720

🚀 DeepGit Lite is live! 🔍✨

Hey folks!
Just launched DeepGit Lite — a lighter version of DeepGit with fewer components under the hood.
It won’t perform quite like the full powerhouse, but it’s great for a quick peek and first-hand feel! ⚙️👀

Give it a spin and tell us what you think!
👉 Try it here zamal/DeepGit-lite
#opensource #DeepGit #gradio #githubresearch

1 reply

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zamal

posted an update 11 days ago

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2499

DeepGit: Your GitHub Gold Digger! 💰🚀
Hey Hugging Face gang! Meet DeepGit—my open-source sidekick that rips through GitHub to snag repos that fit you. Done with dead-end searches? Me too. Built it with LangGraph and some dope tricks:
Embeddings grab the good stuff (HF magic, baby!)

Re-ranking nails the best picks

Snoops docs, code, and buzz in one slick flow

Drops a clean list of hidden gems 💎

Unearth that sneaky ML lib or Python gem—run python app.py or langgraph dev and boom! Peek it at https://github.com/zamalali/DeepGit. Fork it, tweak it, love it—Docker’s in, HF vibes are strong. Drop a 🌟 or a crazy idea—I’m pumped to jam with you all! 🪂

zamal

posted an update about 1 month ago

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2000

🚀 ftBoost is LIVE – Stop Struggling with Fine-Tuning Data!

Alright folks, if you’re tired of manually crafting fine-tuning datasets, ftBoost is here to do the heavy lifting. One-click, LangChain-Groq-powered data augmentation that scales your training data in OpenAI, Gemini, Mistral, and LLaMA formats—automatically.

🔥 What’s inside?
✅ Smart Augmentations – Paraphrasing, back translation, synonym swapping & synthetic noise.
✅ No more JSONL headaches – Auto-formats everything for OpenAI, Gemini, Mistral & LLaMA.
✅ Custom tuning – Adjust similarity, diversity, and fluency in real-time.
✅ Upload, generate, download – That’s it.

⚡ If you’re fine-tuning LLMs, this will save you hours.

🚀 Try it now: 👉 zamal/Finetune-Boost

🌟 Give us a star on GitHub!

Let me know what you think & how it boosts your workflow! 🔥

alvarobartt

posted an update about 2 months ago

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3014

🔥 Agents can do anything! @microsoft Research just announced the release of Magma 8B!

Magma is a new Visual Language Model (VLM) with 8B parameters for multi-modal agents designed to handle complex interactions across virtual and real environments; and it's MIT licensed!

Magma comes with exciting new features such as:
- Introduces the Set-of-Mark and Trace-of-Mark techniques for fine-tuning
- Leverages a large amount of unlabeled video data to learn the spatial-temporal grounding and planning
- A strong generalization and ability to be fine-tuned for other agentic tasks
- SOTA in different multi-modal benchmarks spanning across UI navigation, robotics manipulation, image / video understanding and spatial understanding and reasoning
- Generates goal-driven visual plans and actions for agentic use cases

Model: microsoft/Magma-8B
Technical Report: Magma: A Foundation Model for Multimodal AI Agents (2502.13130)

zamal

posted an update 2 months ago

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604

🚀 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 3 months ago

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1477

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

Hellisotherpeople

authored a paper 3 months ago

OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset

Paper • 2406.14657 • Published Jun 20, 2024

zamal

posted an update 6 months ago

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1832

🚀 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 6 months ago

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2089

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 6 months ago

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1957

🚀 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!

1 reply

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pain

posted an update 7 months ago

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2488

We have published an excellent paper for Arabic CLIP model.

Paper link:
https://aclanthology.org/2024.arabicnlp-1.9/

More information in this website:
https://arabic-clip.github.io/Arabic-CLIP/

All datasets, models, and demo are published to Huggingface:

Arabic-Clip

The codes are published to github:
https://github.com/Arabic-Clip/Arabic-CLIP

1 reply

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alvarobartt

posted an update 8 months ago

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3017

🤗 Serving Meta Llama 3.1 405B on Google Cloud is now possible via the Hugging Face Deep Learning Containers (DLCs) for Text Generation Inference (TGI)

In this post, we showcase how to deploy https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct-FP8 on an A3 instance with 8 x H100 GPUs on Vertex AI

Thanks to the Hugging Face DLCs for TGI and Google Cloud Vertex AI, deploying a high-performance text generation container for serving Large Language Models (LLMs) has never been easier. And we’re not going to stop here – stay tuned as we enable more experiences to build AI with open models on Google Cloud!

Read the full post at https://huggingface.co/blog/llama31-on-vertex-ai

DavidVivancos

posted an update 9 months ago

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1806

#ICLM 2024 is almost there 🔥🔥🔥 PM if you will be in Vienna next week, Glad to catchup with the Hugging Face community there!

I would like to contribute 🎁 by releasing the sixth Knowledge Vault, with 100 lectures visualized from the last 10 years of ICML from 2014 to 2024, (10 from 2024 will be included after the conference) including knowledge graphs for all the Invited Lectures and some extras, with almost 3000 topics represented using AI.

You can explore it here:
🌏 https://theendofknowledge.com/Vaults/6/ICML-2015-2024.html

And you can learn more about the Vaults here:
📝https://www.linkedin.com/pulse/knowledge-vaults-david-vivancos-lbjef/

And previous Vaults relevant to the #huggingface community are:

🌏 [ @lexfridman 2018-2024 Interviews] https://theendofknowledge.com/Vaults/1/Lex100-2024.html

🌏 [ICLR 2014-2023] https://theendofknowledge.com/Vaults/2/ICLR2014-2023.html

🌏 [AIForGood 2017-2024] https://theendofknowledge.com/Vaults/4/AIForGood2017-2024.html

🌏 [CVPR 2015-2024] https://theendofknowledge.com/Vaults/5/CVPR-2015-2024.html

Hope you like them!

And great to see you all at #icml2024 @clem @thomwolf @julien-c and team

radames

posted an update 11 months ago

Post

6731

Thanks to @OzzyGT for pushing the new Anyline preprocessor to https://github.com/huggingface/controlnet_aux. Now you can use the TheMistoAI/MistoLine ControlNet with Diffusers completely.

Here's a demo for you: radames/MistoLine-ControlNet-demo
Super resolution version: radames/Enhance-This-HiDiffusion-SDXL

from controlnet_aux import AnylineDetector

anyline = AnylineDetector.from_pretrained(
    "TheMistoAI/MistoLine", filename="MTEED.pth", subfolder="Anyline"
).to("cuda")

source = Image.open("source.png")
result = anyline(source, detect_resolution=1280)