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yjerniteย  authored a paper about 1 month ago
The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources
yjerniteย  authored a paper about 1 month ago
In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI
yjerniteย  authored a paper about 1 month ago
A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety
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merveย 
posted an update about 17 hours ago
eliebakย 
posted an update 7 days ago
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2891
Super excited to announce that our research team at Hugging Face will be doing an AMA on reddit r/LocalLLaMA.

Come ask any questions to the team behind SmolLM, FineWeb and more! And who knows, maybe thereโ€™ll be a shiny new release to talk about?

Thursday 4th September, 8AM-11AM PST ๐Ÿค—

science
merveย 
posted an update 8 days ago
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large AI labs have dropped so many open models last week ๐Ÿ”ฅ don't miss out on them

โ†’ Apple released on-device vision LMs apple/fastvlm-68ac97b9cd5cacefdd04872e & apple/mobileclip2-68ac947dcb035c54bcd20c47
โ†’ OpenGVLab released InternVL3.5, 32 new vision LMs with one based on gpt-oss! (OS) OpenGVLab/internvl35-68ac87bd52ebe953485927fb
โ†’ MSFT released a killer small TTS model (OS) microsoft/VibeVoice-1.5B

find more herehttps://huggingface.co/collections/merve/august-29-releases-68b5a3754cfb8abf59e2b486
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merveย 
posted an update 14 days ago
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first vision language model built off openai/gpt-oss-20b just dropped! ๐Ÿ”ฅ

InternVL3.5 comes with 32 models ๐Ÿคฏ pre-trained, fine-tuned, aligned in various sizes OpenGVLab/internvl35-68ac87bd52ebe953485927fb
comes with gpt-oss or Qwen3 for LLM part โคต๏ธ
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eliebakย 
posted an update 16 days ago
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541
Motif 2.6B tech report is pretty insane, first time i see a model with differential attention and polynorm trained at scale!

> It's trained on 2.5T of token, with a "data mixture schedule" to continuously adjust the mixture over training.
> They use WSD with a "Simple moving average" averaging the last 6 ckpt every 8B token.
> They trained on Finemath, Fineweb2, DCLM, TxT360.
> Lot of details in the finetuning data they used, for instance they used EvolKit and did some "dataset fusion" to have more compressed knowledge into the data.
> They mention they also tried Normalized GPT, QK-Norm and Cross Layer Attention.

Motif-Technologies/Motif-2.6B
albertvillanovaย 
posted an update 28 days ago
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Latest smolagents release supports GPT-5: build agents that think, plan, and act.
โšก Upgrade now and put GPT-5 to work!
albertvillanovaย 
posted an update 29 days ago
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๐Ÿš€ smolagents v1.21.0 is here!
Now with improved safety in the local Python executor: dunder calls are blocked!
โš ๏ธ Still, not fully isolated: for untrusted code, use a remote executor instead: Docker, E2B, Wasm.
โœจ Many bug fixes: more reliable code.
๐Ÿ‘‰ https://github.com/huggingface/smolagents/releases/tag/v1.21.0
yjerniteย 
authored 3 papers about 1 month ago
merveย 
posted an update about 1 month ago
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3246
GPT-4.1-mini level model right in your iPhone ๐Ÿคฏ

openbmb/MiniCPM-V-4 is only 4B while surpassing GPT-4.1-mini in vision benchmarks ๐Ÿ”ฅ

allows commercial use as well!
merveย 
posted an update about 1 month ago
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we're all sleeping on this OCR model rednote-hilab/dots.ocr ๐Ÿ”ฅ

dots.ocr is a new 3B model with sota performance, support for 100 languages & allowing commercial use! ๐Ÿคฏ

single e2e model to extract image, convert tables, formula, and more into markdown ๐Ÿ“
try it MohamedRashad/Dots-OCR
merveย 
posted an update about 1 month ago
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massive releases and tons of Flux 1. Krea LoRas past week!
here's some of the picks, find more models in collection ๐Ÿซก merve/releases-august-2-6890c14248203522b7d0267f

LLMs ๐Ÿ’ฌ
> Tencent dropped tencent/Hunyuan-7B-Instruct
> Qwen released Qwen/Qwen3-Coder-30B-A3B-Instruct, 30B MoE with 3B params for coding (OS)

vision/multimodal
> RedNote released rednote-hilab/dots.ocr - 3B OCR model (OS)
> Cohere released CohereLabs/command-a-vision-07-2025 - 112B (dense!) VLM for 6 languages
> StepFun-AI shipped stepfun-ai/step3 - 321B MoE VLM (OS)
> Skywork shipped Skywork/Skywork-UniPic-1.5B - new any-to-any model (image+text โ†’ image+text) (OS)
merveย 
posted an update about 1 month ago
IlyasMoutawwakilย 
posted an update about 1 month ago
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3362
๐Ÿš€ Optimum: The Last v1 Release ๐Ÿš€
Optimum v1.27 marks the final major release in the v1 series. As we close this chapter, we're laying the groundwork for a more modular and community-driven future:
- Optimum v2: A lightweight core package for porting Transformers, Diffusers, or Sentence-Transformers to specialized AI hardware/software/accelerators..
- Optimumโ€‘ONNX: A dedicated package where the ONNX/ONNX Runtime ecosystem lives and evolves, faster-moving and decoupled from the Optimum core.

๐ŸŽฏ Why this matters:
- A clearer governance path for ONNX, fostering stronger community collaboration and improved developer experience..
- Enable innovation at a faster pace in a more modular, open-source environment.

๐Ÿ’ก What this means:
- More transparency, broader participation, and faster development driven by the community and key actors in the ONNX ecosystem (PyTorch, Microsoft, Joshua Lochner ๐Ÿ‘€, ...)
- A cleaner, more maintainable core Optimum, focused on extending HF libraries to special AI hardware/software/accelerators tooling and used by our partners (Intel Corporation, Amazon Web Services (AWS), AMD, NVIDIA, FuriosaAI, ...)

๐Ÿ› ๏ธ Major updates I worked on in this release:
โœ… Added support for Transformers v4.53 and SmolLM3 in ONNX/ONNXRuntime.
โœ… Solved batched inference/generation for all supported decoder model architectures (LLMs).

โœจ Big shoutout to @echarlaix for leading the refactoring work that cleanly separated ONNX exporter logic and enabled the creation of Optimumโ€‘ONNX.

๐Ÿ“ Release Notes: https://lnkd.in/gXtE_qji
๐Ÿ“ฆ Optimum : https://lnkd.in/ecAezNT6
๐ŸŽ Optimum-ONNX: https://lnkd.in/gzjyAjSi
#Optimum #ONNX #OpenSource #HuggingFace #Transformers #Diffusers
merveย 
posted an update about 1 month ago
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past week in open AI was insane ๐Ÿ”ฅ here's some of picks, find more here merve/releases-july-25-688768ca47fe3693407e02d1

๐Ÿ’ฌ LLMs & VLMs
> Qwen/Qwen3-235B-A22B-Thinking-2507 had a new update (OS)
> Qwen/Qwen3-Coder-480B-A35B-Instruct is out with 480B total 35B active params ๐Ÿคฏ (OS)
> AllenAI dropped an update to allenai/olmOCR-7B-0725 ๐Ÿ“
> InternLM released internlm/Intern-S1 - 235B Qwen3 MoE + 6B InternViT encoder (OS)
> OmniSVG/OmniSVG is a new SVG generation VLM (OS)

๐Ÿ–ผ๏ธ image/video/3D generation
> WanAI released Wan2.2 series - both T2V and I2V 14B models for high-quality video generation (OS) multimodalart/wan-22-688767e313337b434ed55112
> Tencent dropped tencent/HunyuanWorld-1 - image-to-3D scene generation model
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yjerniteย 
posted an update about 1 month ago
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๐—™๐—ถ๐—ฟ๐˜€๐˜ ๐—š๐—ฃ๐—”๐—œ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น ๐˜„๐—ถ๐˜๐—ต ๐—˜๐—จ ๐——๐—ฎ๐˜๐—ฎ ๐—ง๐—ฟ๐—ฎ๐—ป๐˜€๐—ฝ๐—ฎ๐—ฟ๐—ฒ๐—ป๐—ฐ๐˜† ๐—ง๐—ฒ๐—บ๐—ฝ๐—น๐—ฎ๐˜๐—ฒ? ๐Ÿ‡ช๐Ÿ‡บ

With the release of the EU data transparency template this week, we finally got to see one of the most meaningful artifacts to come out of the AI Act implementation so far (haven't you heard? AI's all about the data! ๐Ÿ“Š๐Ÿ“š)

The impact of the template will depend on how effectively it establishes a minimum meaningful transparency standard for companies that don't otherwise offer any transparency into their handling of e.g. personal data or (anti?-)competitive practices in commercial licensing - we'll see how those play out as new models are released after August 2nd ๐Ÿ‘€


In the meantime, I wanted to see how the template works for a fully open-source + commercially viable model, so I filled it out for the SmolLM3 - which my colleagues at Hugging Face earlier this month ๐Ÿค— ICYMI, it's fully open-source with 3B parameters and performance matching the best similar-size models (I've switched all my local apps from Qwen3 to it, you should too ๐Ÿ’ก)

Verdict: congrats to the European Commission AI Office for making it so straightforward! Fully open and transparent models remain a cornerstone of informed regulation and governance, but the different organizational needs of their developers aren't always properly accounted for in new regulation. In this case, it took me all of two hours to fill out and publish the template (including reading the guidelines) - so kudos for making it feasible for smaller and distributed organizations ๐Ÿ™Œ Definitely a step forward for transparency ๐Ÿ”

To learn more have a look at:

- The SmolLM3 model: HuggingFaceTB/SmolLM3-3B
- Its filled out Public Summary of Training Content: hfmlsoc/smollm3-eu-data-transparency
- And if you're interested, some previous remarks on regulatory minimum meaningful standards for data disclosure: https://huggingface.co/blog/yjernite/naiac-data-transparency
merveย 
posted an update about 1 month ago
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๐Ÿคฏ 241B VLM with apache-2.0 license internlm/Intern-S1

internlm released Intern-S1: multimodal reasoning model based on 235B MoE Qwen3 and 6B InternViT ๐Ÿ˜

benchmarks look great (๐Ÿ‘‘ best model โœ… best open model)
Wauplinย 
posted an update about 2 months ago
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Say hello to hf: a faster, friendlier Hugging Face CLI โœจ

We are glad to announce a long-awaited quality-of-life improvement: the Hugging Face CLI has been officially renamed from huggingface-cli to hf!

So... why this change?

Typing huggingface-cli constantly gets old fast. More importantly, the CLIโ€™s command structure became messy as new features were added over time (upload, download, cache management, repo management, etc.). Renaming the CLI is a chance to reorganize commands into a clearer, more consistent format.

We decided not to reinvent the wheel and instead follow a well-known CLI pattern: hf <resource> <action>. Isn't hf auth login easier to type and remember?

The full rationale, implementation details, and migration notes are in the blog post: https://huggingface.co/blog/hf-cli
sayakpaulย 
posted an update about 2 months ago
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Fast LoRA inference for Flux with Diffusers and PEFT ๐Ÿšจ

There are great materials that demonstrate how to optimize inference for popular image generation models, such as Flux. However, very few cover how to serve LoRAs fast, despite LoRAs being an inseparable part of their adoption.

In our latest post, @BenjaminB and I show different techniques to optimize LoRA inference for the Flux family of models for image generation. Our recipe includes the use of:

1. torch.compile
2. Flash Attention 3 (when compatible)
3. Dynamic FP8 weight quantization (when compatible)
4. Hotswapping for avoiding recompilation during swapping new LoRAs ๐Ÿคฏ

We have tested our recipe with Flux.1-Dev on both H100 and RTX 4090. We achieve at least a *2x speedup* in either of the GPUs. We believe our recipe is grounded in the reality of how LoRA-based use cases are generally served. So, we hope this will be beneficial to the community ๐Ÿค—

Even though our recipe was tested primarily with NVIDIA GPUs, it should also work with AMD GPUs.

Learn the details and the full code here:
https://huggingface.co/blog/lora-fast