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1024m  authored a paper 25 days ago
Uncovering Cultural Representation Disparities in Vision-Language Models
1024m  authored a paper 2 months ago
Robust and Fine-Grained Detection of AI Generated Texts
1024m  authored a paper 2 months ago
Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance
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LocalLLaMA's activity

prithivMLmods 
posted an update about 7 hours ago
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The demo for smoldocling / nanonets ocr / typhoon ocr / monkey ocr explores the document OCR capabilities of various newly released multimodal VLMs in a single space. And if you're experiencing or demoing long document image OCR, kindly use the Smoldocling 256M preview [ Smoldocling is back in demo here. ] 🤗.

✦ Try the demo here : prithivMLmods/Multimodal-OCR2

⤷ MonkeyOCR Recognition : echo840/MonkeyOCR
⤷ Nanonets-OCR-s : nanonets/Nanonets-OCR-s
⤷ SmolDocling-256M-preview : ds4sd/SmolDocling-256M-preview
⤷ typhoon-ocr-7b : scb10x/typhoon-ocr-7b

⤷ Multimodal Implementations : prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0

⤷ Github : https://github.com/PRITHIVSAKTHIUR/Multimodal-OCR2


The community GPU grant was given by Hugging Face — special thanks to them. 🤗🚀



To know more about it, visit the model card of the respective model. !!
prithivMLmods 
posted an update 3 days ago
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The demo for the MonkeyOCR Recognition model, which adopts a Structure-Recognition-Relation (SRR) triplet paradigm & Nanonets-OCR-s a powerful, state-of-the-art image-to-markdown OCR model that goes far beyond traditional text extraction and other experimental document OCR models, is combined into a single space.

✦ Try the demo here : prithivMLmods/core-OCR
✦ Try Nanonets-OCR-s demo here : prithivMLmods/Multimodal-OCR

⤷ MonkeyOCR Recognition : echo840/MonkeyOCR
⤷ docscopeOCR-7B-050425-exp : prithivMLmods/docscopeOCR-7B-050425-exp
⤷ coreOCR-7B-050325-preview : prithivMLmods/coreOCR-7B-050325-preview
⤷ Nanonets-OCR-s : nanonets/Nanonets-OCR-s

⤷ Multimodal Implementations : prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0

Also, include a sample OCR test using the VisionOCR-3B-061125 model and the Qwen2-VL-OCR-2B-Instruct model.
⤷ Blog : https://huggingface.co/blog/prithivMLmods/visionocr-3b-061125-vs-qwen2-vl-ocr-2b-instruct

To know more about it, visit the model card of the respective model. !!
zamal 
posted an update 7 days ago
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Say hallo to GermaNER 💪– a lightweight, high-accuracy NER model for German texts, powered by XLM-RoBERTa + LoRA adapters!
⚡ Fast, efficient, and open-source – perfect for tagging names, places & orgs in real-world German data.
Try it now on Hugging Face 👉 fau/GermaNER
reach-vb 
posted an update 8 days ago
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Excited to onboard FeatherlessAI on Hugging Face as an Inference Provider - they bring a fleet of 6,700+ LLMs on-demand on the Hugging Face Hub 🤯

Starting today, you'd be able to access all those LLMs (OpenAI compatible) on HF model pages and via OpenAI client libraries too! 💥

Go, play with it today: https://huggingface.co/blog/inference-providers-featherless

P.S. They're also bringing on more GPUs to support all your concurrent requests!
Aurelien-Morgan 
posted an update 9 days ago
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💀You can find myself grieving for the next couple hours.
Please send snacks.
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zamal 
posted an update 11 days ago
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🚀 Videoxity is live on Hugging Face! 🎞️
A powerful, modular toolkit for intelligent video manipulation and scene editing.

With Videoxity, you can:

🖼️ Auto-caption keyframes with BLIP

🧠 Filter scenes using natural language (e.g. “remove dog scenes”)

✂️ Seamlessly trim videos with FFmpeg

📊 Generate frame-based summaries

Powered by Groq LLM + LangChain, OpenCV, BLIP, and SentenceTransformers, Videoxity bridges vision and language to give developers full control over video content.
🔧 Built for developers. Feedback welcome!


👉 Try it out here fau/videoxity
leonardlin 
posted an update 16 days ago
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I'm excited to announce the official release of our Shisa V2 405B model:
shisa-ai/shisa-v2-llama3.1-405b

It's the strongest model ever trained in Japan, and even goes toe-to-toe w/ GPT-4o and DeepSeek-V3 in JA MT-Bench.

For all the details, be sure to check out post and overview report here: https://shisa.ai/posts/shisa-v2-405b/
prithivMLmods 
posted an update 20 days ago
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OpenAI, Google, Hugging Face, and Anthropic have released guides and courses on building agents, prompting techniques, scaling AI use cases, and more. Below are 10+ minimalistic guides and courses that may help you in your progress. 📖

⤷ Agents Companion : https://www.kaggle.com/whitepaper-agent-companion
⤷ Building Effective Agents : https://www.anthropic.com/engineering/building-effective-agents
⤷ Guide to building agents by OpenAI : https://cdn.openai.com/business-guides-and-resources/a-practical-guide-to-building-agents.pdf
⤷ Prompt engineering by Google : https://www.kaggle.com/whitepaper-prompt-engineering
⤷ Google: 601 real-world gen AI use cases : https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders
⤷ Prompt engineering by IBM : https://www.ibm.com/think/topics/prompt-engineering-guide
⤷ Prompt Engineering by Anthropic : https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview
⤷ Scaling AI use cases : https://cdn.openai.com/business-guides-and-resources/identifying-and-scaling-ai-use-cases.pdf
⤷ Prompting Guide 101 : https://services.google.com/fh/files/misc/gemini-for-google-workspace-prompting-guide-101.pdf
⤷ AI in the Enterprise by OpenAI : https://cdn.openai.com/business-guides-and-resources/ai-in-the-enterprise.pdf

by HF🤗 :
⤷ AI Agents Course by Huggingface : https://huggingface.co/learn/agents-course/unit0/introduction
⤷ Smol-agents Docs : https://huggingface.co/docs/smolagents/en/tutorials/building_good_agents
⤷ MCP Course by Huggingface : https://huggingface.co/learn/mcp-course/unit0/introduction
⤷ Other Course (LLM, Computer Vision, Deep RL, Audio, Diffusion, Cookbooks, etc..) : https://huggingface.co/learn
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prithivMLmods 
posted an update 22 days ago
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Just made a demo for Cosmos-Reason1, a physical AI model that understands physical common sense and generates appropriate embodied decisions in natural language through long chain-of-thought reasoning. Also added video understanding support to it. 🤗🚀

✦ Try the demo here : prithivMLmods/DocScope-R1

⤷ Cosmos-Reason1-7B : nvidia/Cosmos-Reason1-7B
⤷ docscopeOCR-7B-050425-exp : prithivMLmods/docscopeOCR-7B-050425-exp
⤷ Captioner-Relaxed : Ertugrul/Qwen2.5-VL-7B-Captioner-Relaxed

⤷ Multimodal Implementations : prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0

⤷ GitHub :
• https://github.com/PRITHIVSAKTHIUR/Cosmos-x-DocScope
• https://github.com/PRITHIVSAKTHIUR/Nvidia-Cosmos-Reason1-Demo.

To know more about it, visit the model card of the respective model. !!
1024m 
authored a paper 25 days ago
leonardlin 
posted an update 27 days ago
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BTW, in case anyone wants to kick the tires, test their 日本語, I have our Shisa V2 405B model up and running temporarily: https://chat.shisa.ai/
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prithivMLmods 
posted an update about 1 month ago
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Got access to Google's all-new Gemini Diffusion a state-of-the-art text diffusion model. It delivers the performance of Gemini 2.0 Flash-Lite at 5x the speed, generating over 1000 tokens in a fraction of a second and producing impressive results. Below are some initial outputs generated using the model. ♊🔥

Gemini Diffusion Playground ✦ : https://deepmind.google.com/frontiers/gemini-diffusion

Get Access Here : https://docs.google.com/forms/d/1aLm6J13tAkq4v4qwGR3z35W2qWy7mHiiA0wGEpecooo/viewform?edit_requested=true

🔗 To know more, visit: https://deepmind.google/models/gemini-diffusion/
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prithivMLmods 
posted an update about 1 month ago
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The more optimized explicit content filters with lightweight 𝙜𝙪𝙖𝙧𝙙 models trained based on siglip2 patch16 512 and vit patch16 224 for illustration and explicit content classification for content moderation in social media, forums, and parental controls for safer browsing environments. this version fixes the issues in the previous release, which lacked sufficient resources. 🚀

⤷ Models :
→ siglip2 mini explicit content : prithivMLmods/siglip2-mini-explicit-content [recommended]
→ vit mini explicit content : prithivMLmods/vit-mini-explicit-content

⤷ Building image safety-guard models : strangerguardhf

⤷ Datasets :
→ nsfw multidomain classification : strangerguardhf/NSFW-MultiDomain-Classification
→ nsfw multidomain classification v2.0 : strangerguardhf/NSFW-MultiDomain-Classification-v2.0

⤷ Collection :
→ Updated Versions [05192025] : prithivMLmods/explicit-content-filters-682aaa4733e378561925ca2b
→ Previous Versions : prithivMLmods/siglip2-content-filters-042025-final-680fe4aa1a9d589bf2c915ff

Find a collections inside the collection.👆

To know more about it, visit the model card of the respective model.
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reach-vb 
posted an update about 1 month ago
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hey hey @mradermacher - VB from Hugging Face here, we'd love to onboard you over to our optimised xet backend! 💥

as you know we're in the process of upgrading our storage backend to xet (which helps us scale and offer blazingly fast upload/ download speeds too): https://huggingface.co/blog/xet-on-the-hub and now that we are certain that the backend can scale with even big models like Llama 4/ Qwen 3 - we;re moving to the next phase of inviting impactful orgs and users on the hub over as you are a big part of the open source ML community - we would love to onboard you next and create some excitement about it in the community too!

in terms of actual steps - it should be as simple as one of the org admins to join hf.co/join/xet - we'll take care of the rest.

p.s. you'd need to have a the latest hf_xet version of huggingface_hub lib but everything else should be the same: https://huggingface.co/docs/hub/storage-backends#using-xet-storage

p.p.s. this is fully backwards compatible so everything will work as it should! 🤗
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Aurelien-Morgan 
posted an update about 1 month ago
prithivMLmods 
posted an update about 1 month ago
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Models for detecting images generated by diffusion models (Flux.1, SDXL, ..) are trained or fine-tuned using image classification models for content moderation. These models use datasets available on the Hub. For identifying AI-generated images or moderating visual content, the recommended model is OpenSDI-Flux.1-SigLIP2.😺🧨

Models : prithivMLmods/OpenSDI-Flux.1-SigLIP2 [Best approach for AI [Diffusion Generated] vs. real image classification] prithivMLmods/OpenSDI-SD2.1-SigLIP2 prithivMLmods/OpenSDI-SD3-SigLIP2 prithivMLmods/OpenSDI-SD1.5-SigLIP2 prithivMLmods/OpenSDI-SDXL-SigLIP2

Datasets : nebula/OpenSDI_test madebyollin/megalith-10m

Collection : prithivMLmods/opensdi-diffusion-generated-image-classification-682488a3a3e5be7083db3383

Find a collections inside the collection.👆

To know more about it, visit the model card of the respective model.
prithivMLmods 
posted an update about 1 month ago
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Dropping some image classification models for content moderation and classifiers trained with datasets available on the Hub. All are fine-tuned on the siglip2 backbone, (competitions AIOrNot, Imagenette, and Driver-Drowsiness). Models and datasets are listed below:

🤗Models :
AI or Not : prithivMLmods/AIorNot-SigLIP2
Driver Drowsiness Detection : prithivMLmods/DOZE-GUARD-RLDD
Subset 10 ImageNet : prithivMLmods/IMAGENETTE

🥊Datasets :
+ competitions/aiornot
+ akahana/Driver-Drowsiness-Dataset
+ frgfm/imagenette

🔗Collection :
[The previous collection of models is also listed in the same collection, so you can find more models focused on image classification tasks.]

- prithivMLmods/multiclass-image-classification-05142025-68234c8010a9350a4d6739b5

Find a collections inside the collection.🤪👆

To know more about it, visit the model card of the respective model.
prithivMLmods 
posted an update about 1 month ago
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Dropping some image classification models for content moderation, balancers, and classifiers trained on synthetic datasets—along with others based on datasets available on the Hub. Also loaded a few low-rank datasets for realistic gender portrait classification and document-type classifiers, all fine-tuned on the SigLIP-2 Patch-16 224 backbone. Models and datasets are listed below:

🤗Models & Datasets :

Realistic Gender Classification : prithivMLmods/Realistic-Gender-Classification
⎙ prithivMLmods/Realistic-Portrait-Gender-1024px
Document Type Detection : prithivMLmods/Document-Type-Detection
⎙ prithivMLmods/Document-Type-Detection
Face Mask Detection : prithivMLmods/Face-Mask-Detection
⎙ DamarJati/Face-Mask-Detection
Alzheimer Stage Classifier : prithivMLmods/Alzheimer-Stage-Classifier
⎙ SilpaCS/Augmented_alzheimer
Bone Fracture Detection : prithivMLmods/Bone-Fracture-Detection
⎙ Hemg/bone-fracture-detection
GiD Land Cover Classification : prithivMLmods/GiD-Land-Cover-Classification
⎙ jonathan-roberts1/GID

🤗Collection : prithivMLmods/siglip2-05102025-681c2b0e406f0740a993fc1c

To know more about it, visit the model card of the respective model.
Nymbo 
posted an update about 1 month ago
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Haven't seen this posted anywhere - Llama-3.3-8B-Instruct is available on the new Llama API. Is this a new model or did someone mislabel Llama-3.1-8B?
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prithivMLmods 
posted an update about 1 month ago
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Well, here’s the updated version with the 20,000+ entry sampled dataset for Watermark Filter Content Moderation models incl. [Food25, Weather, Watermark, Marathi/Hindi Sign Language Detection], post-trained from the base models: sigLip2 patch16 224 — now with mixed aspect ratios for better performance and reduced misclassification. 🔥

Models :
➮ Watermark-Detection : prithivMLmods/Watermark-Detection-SigLIP2
⌨︎ Watermark Detection & Batch Image Processing Experimentals, Colab Notebook : https://colab.research.google.com/drive/1mlQrSsSjkGimUt0VyRi3SoWMv8OMyvw3?usp=drive_link
➮ Weather-Image-Classification : prithivMLmods/Weather-Image-Classification
➮ TurkishFoods-25 : prithivMLmods/TurkishFoods-25
➮ Marathi-Sign-Language-Detection : prithivMLmods/Marathi-Sign-Language-Detection
➮ Hindi-Sign-Language-Detection : prithivMLmods/Hindi-Sign-Language-Detection

Datasets :
Watermark : qwertyforce/scenery_watermarks
Weather : prithivMLmods/WeatherNet-05-18039
Turkish Foods 25 : yunusserhat/TurkishFoods-25
Marathi Sign Language : VinayHajare/Marathi-Sign-Language
Hindi Sign Language : Vedant3907/Hindi-Sign-Language-Dataset

Collection : prithivMLmods/content-filters-siglip2-vit-68197e3357d4de18fb3b4d2b