That Time I got Reincarnated as a Hugging Face Organization

community

AI & ML interests

LowRes animated waifus (✿◡‿◡)

Recent Activity

Lolimipsu  updated a Space 22 days ago
lowres/README
not-lain  updated a Space about 2 months ago
lowres/SigLIP_Tagger
View all activity

lowres's activity

louisbrulenaudet 
posted an update 8 days ago
view post
Post
2997
I am pleased to introduce my first project built upon Hugging Face’s smolagents framework, integrated with Alpaca for financial market analysis automation 🦙🤗

The project implements technical indicators such as the Relative Strength Index (RSI) and Bollinger Bands to provide momentum and volatility analysis. Market data is retrieved through the Alpaca API, enabling access to historical price information across various timeframes.

AI-powered insights are generated using Hugging Face’s inference API, facilitating the analysis of market trends through natural language processing with DuckDuckGo search integration for real-time sentiment analysis based on financial news 🦆

Link to the GitHub project: https://github.com/louisbrulenaudet/agentic-market-tool

eienmojiki 
posted an update 16 days ago
Lolimipsu 
updated a Space 22 days ago
zamal 
posted an update 24 days ago
view post
Post
480
🚀 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
·
ameerazam08 
posted an update 25 days ago
zamal 
posted an update about 1 month ago
view post
Post
1447
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
not-lain 
updated a Space about 2 months ago
DamarJati 
posted an update about 2 months ago
view post
Post
2861
Happy New Year 2025 🤗
For the Huggingface community.
lunarflu 
posted an update 3 months ago
louisbrulenaudet 
posted an update 3 months ago
view post
Post
1996
I’ve published a new dataset to simplify model merging 🤗

This dataset facilitates the search for compatible architectures for model merging with @arcee_ai’s mergekit, streamlining the automation of high-performance merge searches 📖

Dataset : louisbrulenaudet/mergekit-configs
  • 1 reply
·
louisbrulenaudet 
posted an update 4 months ago
view post
Post
1342
Introducing Lemone-router, a series of classification models designed to produce an optimal multi-agent system for different branches of tax law.

Trained on a base of 49k lines comprising a set of synthetic questions generated by GPT-4 Turbo and Llama 3.1 70B, which have been further refined through evol-instruction tuning and manual curation and authority documents, these models are based on an 8-category decomposition of the classification scheme derived from the Bulletin officiel des finances publiques - impôts :

label2id = {
    "Bénéfices professionnels": 0,
    "Contrôle et contentieux": 1,
    "Dispositifs transversaux": 2,
    "Fiscalité des entreprises": 3,
    "Patrimoine et enregistrement": 4,
    "Revenus particuliers": 5,
    "Revenus patrimoniaux": 6,
    "Taxes sur la consommation": 7
}
	
id2label = {
    0: "Bénéfices professionnels",
    1: "Contrôle et contentieux",
    2: "Dispositifs transversaux",
    3: "Fiscalité des entreprises",
    4: "Patrimoine et enregistrement",
    5: "Revenus particuliers",
    6: "Revenus patrimoniaux",
    7: "Taxes sur la consommation"
}

It achieves the following results on the evaluation set:
- Loss: 0.4734
- Accuracy: 0.9191

Link to the collection: louisbrulenaudet/lemone-router-671cce21d6410f3570514762
zamal 
posted an update 4 months ago
view post
Post
1828
🚀 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! 🚀✨

louisbrulenaudet 
posted an update 4 months ago
view post
Post
3128
🚨 I have $3,500 in Azure credits, including access to an H100 (96 Go), expiring on November 12, 2024.

I won’t be able to use it all myself, so I’m reaching out to the @huggingface community: Are there any open-source projets with data ready for some compute power?

Let’s collaborate and make the most of it together 🔗
·
zamal 
posted an update 4 months ago
view post
Post
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 5 months ago
view post
Post
1954
🚀 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
·
louisbrulenaudet 
posted an update 5 months ago
view post
Post
2138
My biggest release of the year: a series of 7 specialized embedding models for information retrieval within tax documents, is now available for free on Hugging Face 🤗

These new models aim to offer an open source alternative for in-domain semantic search from large text corpora and will improve RAG systems and context addition for large language models.

Trained on more than 43 million tax tokens derived from semi-synthetic and raw-synthetic data, enriched by various methods (in particular MSFT's evol-instruct by @intfloat ), and corrected by humans, this project is the fruit of hundreds of hours of work and is the culmination of a global effort to open up legal technologies that has only just begun.

A big thank you to Microsoft for Startups for giving me access to state-of-the-art infrastructure to train these models, and to @julien-c , @clem 🤗, @thomwolf and the whole HF team for the inference endpoint API and the generous provision of Meta LLama-3.1-70B. Special thanks also to @tomaarsen for his invaluable advice on training embedding models and Loss functions ❤️

Models are available on my personal HF page, into the Lemone-embed collection: louisbrulenaudet/lemone-embed-66fdc24000df732b395df29b
  • 1 reply
·
louisbrulenaudet 
posted an update 6 months ago
view post
Post
2610
The Romulus model series has been released on Hugging Face, continually pre-trained on 34,864,949 tokens of French laws and intended to serve as a foundation for fine-tuning on labeled data 🤗

The training code, dataset and model weights are open and available free on HF and the training was based on H100 provided by Microsoft for Startups using Unsloth AI by @danielhanchen and @shimmyshimmer 🦥

Link to the base model: louisbrulenaudet/Romulus-cpt-Llama-3.1-8B-v0.1

Link to the instruct model: louisbrulenaudet/Romulus-cpt-Llama-3.1-8B-v0.1-Instruct

Link to the dataset: louisbrulenaudet/Romulus-cpt-fr

Please note that these models have not been aligned for the production of usable texts as they stand, and will certainly need to be refined for the desired tasks in order to produce satisfactory results.
  • 1 reply
·
louisbrulenaudet 
posted an update 6 months ago
view post
Post
1578
An example of the application of LegalKit is the production of knowledge graphs, here is a demo Space 🔗

With the update of the French legal code data model uploaded to 🤗 and the introduction of a column dedicated to HTML text, it's now easy to extract links between different articles and produce complex graphs with just a few lines of Python.

This simplified demo highlights the ease of implementation and creative potential, and enables the generation of complete data sets, although requiring a powerful graphics card for display. The framework used for the moment is D3.js, but perhaps other solutions are possible. I'd be delighted to hear your suggestions, and look forward to hearing from the community.

Link to the 🤗 Space: louisbrulenaudet/legalkit-knowledge-graph
  • 2 replies
·