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nielsr  new activity 2 days ago
huggan/flowers-102-categories:Labels for the images
gagan3012  authored a paper 29 days ago
Leveraging Vision-Language Pre-training for Human Activity Recognition in Still Images
gagan3012  authored a paper about 2 months ago
Date Fragments: A Hidden Bottleneck of Tokenization for Temporal Reasoning
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merve 
posted an update about 14 hours ago
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203
Fine-tune Gemma3n on videos with audios inside with Colab A100 🔥
Just dropped the notebook where you can learn how to fine-tune Gemma3n on images+audio+text at the same time!

keep in mind, it's made for educational purposes 🫡 we do LoRA, audio resampling & video downsampling to be able to train <40GB VRAM

stretch modalities and unfreeze layers as you wish! 🙏🏻 merve/smol-vision
nielsr 
in huggan/flowers-102-categories 2 days ago

Labels for the images

1
#3 opened 5 days ago by
afazrihady
merve 
posted an update 3 days ago
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2234
past week had huuuge releases 💗
here's our picks 🔥 find more models, datasets, demos here merve/releases-july-11-68750452c358c98b0fa663f7

> moonshotai/Kimi-K2-Instruct is the new sota LLM with 1T total 32B active parameters 🤯

> HuggingFaceTB/SmolLM3-3B is the new best LM for it's size, offers thinking mode 💭 as well as the dataset HuggingFaceTB/smoltalk2

> Alibaba-NLP/WebSailor-3B is the new agentic LLM for complex browsing

> Google DeepMind released medical vision LMs with an agentic doctor-patient app google/medgemma-release-680aade845f90bec6a3f60c4

> fal released a LoRA to improve details on face images fal/Realism-Detailer-Kontext-Dev-LoRA
merve 
posted an update 8 days ago
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3028
GitHub refuses to render notebooks for a long time now 💔

so smol-vision now lives in Hugging Face model repository 🤗 merve/smol-vision
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merve 
posted an update 9 days ago
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3374
ByteDance released Tar 1.5B and 7B: image-text in image-text out models, fully open-source 👏 ByteDance-Seed/tar-6864cf0d9fe59a3b91cc4260

They have an image tokenizer unified with text, and they de-tokenize using either of two models (LLM and diffusion)
The model is actually a full LLM (Qwen2), the tokenizer converts image tokens 🤯
merve 
posted an update 10 days ago
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3629
Huge drops in open AI past week!
Find more models, datasets, demos here merve/releases-july-4-686bcc54ed7c45c341fbf654
Some of our picks 🫡
⏯️ BAAI/MTVCraft is a new Veo3-like text-to-video model, demo is here BAAI/MTVCraft
🧑🏻‍💻 apple/diffucoder-6868139f56672ae046fe04e8 is a new family of diffusion LLMs (7B base and instruct) for coding
🗣️ kyutai/tts-1.6b-en_fr is a new small TTS model for English and France
👀 aharley/alltracker is a new pixel tracking model by Stanford, demo is here aharley/alltracker
📖 racineai/OGC_MEGA_MultiDomain_DocRetrieval is a new large visual document retrieval dataset
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merve 
posted an update 15 days ago
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916
SOOOO MANY MODEL RELEASES 😍
Here's some picks from past week 🤗

> ByteDance/XVerse is a new identity preserving image generation model 🖼️
> google/gemma-3n-E4B-it, any-to-text model supported by transformers 🤗
> nvidia/llama-nemoretriever-colembed-3b-v1 two new state-of-the-art visual document retrievers 📑
> New version of Dia TTS model is up nari-labs/Dia-1.6B-0626
> Black Forest Labs releases Kontext benchmark black-forest-labs/kontext-bench

Find more here merve/releases-june-27-6864e8eb17f7e3a8b444083c
merve 
posted an update 15 days ago
merve 
posted an update 17 days ago
merve 
posted an update 21 days ago
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595
Dataset Viewer for PDFs just landed on Hugging Face 📖🤗 you can now preview all the PDFs easier than before!

on top of this, there's PdfFolder format to load the PDF datasets quicker 💨
> to use it, your dataset should follow a directory format like folder/train/doc1.pdf, folder/train/doc1.pdf
> if you want to include bounding boxes, labels etc. you can keep them in a metadata.csv file in the same folder 🤝

read document dataset docs https://huggingface.co/docs/datasets/main/en/document_dataset
check all the document datasets here https://huggingface.co/datasets?modality=modality:document&sort=trending 📖
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merve 
posted an update 23 days ago
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we've merged LightGlue keypoint matcher to Hugging Face transformers! it allows commercial use when paired with an open-source keypoint detector 🙏🏻

it works very well, try it yourself: ETH-CVG/LightGlue

here's an in-the-wild test with two images of the same place ⤵️
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merve 
posted an update 24 days ago
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Release picks of the past week is here! Find more models, datasets, Spaces here merve/june-20-releases-68594824d1f4dfa61aee3433

🖼️ VLMs/OCR
> moonshotai/Kimi-VL-A3B-Thinking-2506 is a powerful reasoning vision LM, 3B active params, smarter with less tokens, supports long documents, videos 👏 (OS)
> nanonets/Nanonets-OCR-s is 3.75B params OCR model based on Qwen2.5VL-3B-Instruct (OS)

💬 LLMs
> moonshotai/Kimi-Dev-72B is a strong coding model based on Qwen2.5-72B (OS)
> Mistral released mistralai/Mistral-Small-3.2-24B-Instruct-2506, an update to their former model with better function calling & instruction following (OS)

🗣️ Audio
> Google released google/magenta-realtime, real time music generation & audio synthesis (cc-by-4)
> kyutai released new speech-to-text models that come in 1B & 2B ( kyutai/stt-1b-en_fr, stt-2b-en_fr) with 0.5s and 2.5s delay

3D
> Tencent released tencent/Hunyuan3D-2.1 an image-to-3D model (see below)
merve 
posted an update 25 days ago
merve 
posted an update 27 days ago
clem 
posted an update 27 days ago
merve 
posted an update 28 days ago
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stop using VLMs blindly ✋🏻

compare different VLM outputs on a huge variety of inputs (from reasoning to OCR!) 🔥 visionLMsftw/comparevlms

> has support for multiple VLMs: google/gemma-3-27b-it, Qwen/Qwen2.5-VL-7B-Instruct, Qwen/Qwen2.5-VL-32B-Instruct, meta-llama/Llama-4-Maverick-17B-128E-Instruct, HuggingFaceTB/SmolVLM2-2.2B-Instruct
> recommend us new models or inputs, we'll add 🫡

so far I figured out
> for fact-checks, you need a relatively bigger size (7B is ok!)
> Gemma 3 gets downgrade without pan and scan (especially for 📑)
> Qwen2.5VL-32B is very talkative, great for reasoning but not good for simple tasks 🗣️
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merve 
posted an update 29 days ago
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3627
Releases of the past week are here merve/releases-june-13-6852c3c1eaf1e0c24c958860

Here's our picks 🤓
So many interesting models released past week in open AI! 🤖

🖼️ Computer Vision/VLMs
> nanonets/Nanonets-OCR-s is the new state-of-the-art OCR model that can handle checkboxes, watermarks, tables (OS)
> Meta released facebook/v-jepa-2-6841bad8413014e185b497a6, new sota video embeddings with two new classification models (OS)
> ByteDance-Seed/SeedVR2-3B is a new 3B video restoration model (OS)

Audio
> Stepfun released stepfun-ai/Step-Audio-AQAA, new large (137B 🤯) audio language model that takes in audio and generates audio (OS)

🤖 Robotics
> nvidia released nvidia/GR00T-N1.5-3B, new open foundation vision language action model

3D
> tencent/Hunyuan3D-2.1 is the new version of Hunyuan by Tencent that can generate 3D assets from text and image prompts
gagan3012 
authored a paper 29 days ago
merve 
posted an update 30 days ago
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3561
IN: video fine-tuning support for facebook V-JEPA 2 in HF transformers 🔥

it comes with
> four models fine-tuned on Diving48 and SSv2 dataset facebook/v-jepa-2-6841bad8413014e185b497a6
> FastRTC demo on V-JEPA2 SSv2 qubvel-hf/vjepa2-streaming-video-classification
> fine-tuning script on UCF-101 https://gist.github.com/ariG23498/28bccc737c11d1692f6d0ad2a0d7cddb
> fine-tuning notebook on UCF-101 https://colab.research.google.com/drive/16NWUReXTJBRhsN3umqznX4yoZt2I7VGc?usp=sharing
we're looking forward to see what you will build! 🤗
merve 
posted an update about 1 month ago
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#CVPR2025 Paper Picks #1
VisionZip is a compression technique that reduces number of visual tokens to improve performance AND prefill time for vision language models
demo: Senqiao/VisionZip
paper: VisionZip: Longer is Better but Not Necessary in Vision Language Models (2412.04467)
most of the image tokens are redundant for the LLM, so the authors ask "are all visual tokens necessary?"

the method is simple:
find which tokens have the highest attention score, merge rest of the tokens based on similarity, then merge both

their method is both training-free and for fine-tuning
the authors report 5 point improvement on average of vision language tasks + 8x improvement in prefilling time for Llava-Next 7B and 13B 🤯

removing redundant tokens improve image token quality too 🥹