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sayakpaulΒ
updated
a
dataset
1 day ago
evijitΒ
updated
a
dataset
1 day ago
nielsrΒ
updated
a
Space
2 days ago
jsulzΒ
updated
a
dataset
2 days ago
[FEEDBACK] Follow
14
#14 opened over 1 year ago
by
victor
mishigΒ
updated
a
Space
3 days ago
Post
4051
We just crossed 1,500,000 public models on Hugging Face (and 500k spaces, 330k datasets, 50k papers). One new repository is created every 15 seconds. Congratulations all!
- 3 replies
Post
1511
SEA-VLπ₯ an OPEN dataset bridge the AI culture gap in Southeast Asia!
Paper: Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia (2503.07920)
β¨1.28M+ culturally relevant images
β¨85% accuracy in auto-collected images
β¨Tracking underrepresented SEA languages & traditions
Paper: Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia (2503.07920)
β¨1.28M+ culturally relevant images
β¨85% accuracy in auto-collected images
β¨Tracking underrepresented SEA languages & traditions
Post
1748
Open Sora 2.0 is out π₯
hpcai-tech/open-sora-20-67cfb7efa80a73999ccfc2d5
β¨ 11B with Apache2.0
β¨ Low training cost - $200k
β¨ open weights, code and training workflow
hpcai-tech/open-sora-20-67cfb7efa80a73999ccfc2d5
β¨ 11B with Apache2.0
β¨ Low training cost - $200k
β¨ open weights, code and training workflow
Post
1244
It's finally here β€οΈ
Build faster than ever with lightning fast upload and download speeds starting today on the Hub β‘
Xet storage is rolling out access across the Hub - join the waitlist here https://huggingface.co/join/xet
You can apply for yourself, or your entire organization. Head over to your account settings for more information or join anywhere you see the Xet logo on a repository you know.
Have questions? Join the conversation below π or open a discussion on the Xet team page xet-team/README
Build faster than ever with lightning fast upload and download speeds starting today on the Hub β‘
Xet storage is rolling out access across the Hub - join the waitlist here https://huggingface.co/join/xet
You can apply for yourself, or your entire organization. Head over to your account settings for more information or join anywhere you see the Xet logo on a repository you know.
Have questions? Join the conversation below π or open a discussion on the Xet team page xet-team/README
-
- 6 replies
Upload folder using huggingface_hub
1
#450 opened 4 days ago
by
a-r-r-o-w
abidlabsΒ
updated
a
dataset
4 days ago
lewtunΒ
authored
a
paper
5 days ago
Post
2155
We've kept pushing our Open-R1 project, an open initiative to replicate and extend the techniques behind DeepSeek-R1.
And even we were mind-blown by the results we got with this latest model we're releasing: β‘οΈOlympicCoder ( open-r1/OlympicCoder-7B and open-r1/OlympicCoder-32B)
It's beating Claude 3.7 on (competitive) programming βa domain Anthropic has been historically really strong atβ and it's getting close to o1-mini/R1 on olympiad level coding with just 7B parameters!
And the best part is that we're open-sourcing all about its training dataset, the new IOI benchmark, and more in our Open-R1 progress report #3: https://huggingface.co/blog/open-r1/update-3
Datasets are are releasing:
- open-r1/codeforces
- open-r1/codeforces-cots
- open-r1/ioi
- open-r1/ioi-test-cases
- open-r1/ioi-sample-solutions
- open-r1/ioi-cots
- open-r1/ioi-2024-model-solutions
And even we were mind-blown by the results we got with this latest model we're releasing: β‘οΈOlympicCoder ( open-r1/OlympicCoder-7B and open-r1/OlympicCoder-32B)
It's beating Claude 3.7 on (competitive) programming βa domain Anthropic has been historically really strong atβ and it's getting close to o1-mini/R1 on olympiad level coding with just 7B parameters!
And the best part is that we're open-sourcing all about its training dataset, the new IOI benchmark, and more in our Open-R1 progress report #3: https://huggingface.co/blog/open-r1/update-3
Datasets are are releasing:
- open-r1/codeforces
- open-r1/codeforces-cots
- open-r1/ioi
- open-r1/ioi-test-cases
- open-r1/ioi-sample-solutions
- open-r1/ioi-cots
- open-r1/ioi-2024-model-solutions
Post
1223
Spark TTS πNew OPEN TTS model that can generate any voice with just seconds of audio!
Released by SparkAudio communityπ₯
Modelπ SparkAudio/Spark-TTS-0.5B
Paperπ Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens (2503.01710)
β¨ Supports English & Chinese
β¨ BiCodec Speech Codec: Enables precise voice control by separating semantics & speaker attributes
Released by SparkAudio communityπ₯
Modelπ SparkAudio/Spark-TTS-0.5B
Paperπ Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens (2503.01710)
β¨ Supports English & Chinese
β¨ BiCodec Speech Codec: Enables precise voice control by separating semantics & speaker attributes
Post
1309
R1-Omniπ₯RLVR-Powered Multimodal LLM released by Alibaba
Model: StarJiaxing/R1-Omni-0.5B
Paper: R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcing Learning (2503.05379)
β¨0.5B with Apache2.0
β¨ Improve emotion recognition with visual and audio cues
Model: StarJiaxing/R1-Omni-0.5B
Paper: R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcing Learning (2503.05379)
β¨0.5B with Apache2.0
β¨ Improve emotion recognition with visual and audio cues
- 1 reply
freddyaboultonΒ
posted
an
update
5 days ago
Post
1699
Privacy matters when talking to AI! π
We've just added a microphone mute button to FastRTC in our latest update (v0.0.14). Now you control exactly what your LLM hears.
Plus lots more features in this release! Check them out:
https://github.com/freddyaboulton/fastrtc/releases/tag/0.0.14
We've just added a microphone mute button to FastRTC in our latest update (v0.0.14). Now you control exactly what your LLM hears.
Plus lots more features in this release! Check them out:
https://github.com/freddyaboulton/fastrtc/releases/tag/0.0.14
Post
1906
Introducing OlympicCoder: a series of open reasoning models that can solve olympiad-level programming problems π§βπ»
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger πͺ
Together with the models, we are releasing:
πCodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
π IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger πͺ
Together with the models, we are releasing:
πCodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
π IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 1 reply
Post
2218
Important notice π¨
For Inference Providers who have built support for our Billing API (currently: Fal, Novita, HF-Inference β with more coming soon), we've started enabling Pay as you go (=PAYG)
What this means is that you can use those Inference Providers beyond the free included credits, and they're charged to your HF account.
You can see it on this view: any provider that does not have a "Billing disabled" badge, is PAYG-compatible.
For Inference Providers who have built support for our Billing API (currently: Fal, Novita, HF-Inference β with more coming soon), we've started enabling Pay as you go (=PAYG)
What this means is that you can use those Inference Providers beyond the free included credits, and they're charged to your HF account.
You can see it on this view: any provider that does not have a "Billing disabled" badge, is PAYG-compatible.
Post
6269
An assembly of 18 European companies, labs, and universities have banded together to launch πͺπΊ EuroBERT! It's a state-of-the-art multilingual encoder for 15 European languages, designed to be finetuned for retrieval, classification, etc.
πͺπΊ 15 Languages: English, French, German, Spanish, Chinese, Italian, Russian, Polish, Portuguese, Japanese, Vietnamese, Dutch, Arabic, Turkish, Hindi
3οΈβ£ 3 model sizes: 210M, 610M, and 2.1B parameters - very very useful sizes in my opinion
β‘οΈ Sequence length of 8192 tokens! Nice to see these higher sequence lengths for encoders becoming more common.
βοΈ Architecture based on Llama, but with bi-directional (non-causal) attention to turn it into an encoder. Flash Attention 2 is supported.
π₯ A new Pareto frontier (stronger *and* smaller) for multilingual encoder models
π Evaluated against mDeBERTa, mGTE, XLM-RoBERTa for Retrieval, Classification, and Regression (after finetuning for each task separately): EuroBERT punches way above its weight.
π Detailed paper with all details, incl. data: FineWeb for English and CulturaX for multilingual data, The Stack v2 and Proof-Pile-2 for code.
Check out the release blogpost here: https://huggingface.co/blog/EuroBERT/release
* EuroBERT/EuroBERT-210m
* EuroBERT/EuroBERT-610m
* EuroBERT/EuroBERT-2.1B
The next step is for researchers to build upon the 3 EuroBERT base models and publish strong retrieval, zero-shot classification, etc. models for all to use. I'm very much looking forward to it!
πͺπΊ 15 Languages: English, French, German, Spanish, Chinese, Italian, Russian, Polish, Portuguese, Japanese, Vietnamese, Dutch, Arabic, Turkish, Hindi
3οΈβ£ 3 model sizes: 210M, 610M, and 2.1B parameters - very very useful sizes in my opinion
β‘οΈ Sequence length of 8192 tokens! Nice to see these higher sequence lengths for encoders becoming more common.
βοΈ Architecture based on Llama, but with bi-directional (non-causal) attention to turn it into an encoder. Flash Attention 2 is supported.
π₯ A new Pareto frontier (stronger *and* smaller) for multilingual encoder models
π Evaluated against mDeBERTa, mGTE, XLM-RoBERTa for Retrieval, Classification, and Regression (after finetuning for each task separately): EuroBERT punches way above its weight.
π Detailed paper with all details, incl. data: FineWeb for English and CulturaX for multilingual data, The Stack v2 and Proof-Pile-2 for code.
Check out the release blogpost here: https://huggingface.co/blog/EuroBERT/release
* EuroBERT/EuroBERT-210m
* EuroBERT/EuroBERT-610m
* EuroBERT/EuroBERT-2.1B
The next step is for researchers to build upon the 3 EuroBERT base models and publish strong retrieval, zero-shot classification, etc. models for all to use. I'm very much looking forward to it!
- 1 reply