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Post #2317
404
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HU Hugging Face
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Post #2316
404
This post (sticker, poll or similar) has no web preview. Open in Telegram
Post #2315
1.42K
- 😁 2
Post #2314
1.99K
Hugging Face (Twitter)
RT @evijit: Today, @evaluatingevals is introducing Every Eval Ever, a unified, open data format and public dataset for AI evaluation results.
RT @evijit: Today, @evaluatingevals is introducing Every Eval Ever, a unified, open data format and public dataset for AI evaluation results.
Post #2313
1.81K
Hugging Face (Twitter)
RT @Cohere_Labs: Introducing ✨Tiny Aya✨, a family of massively multilingual small language models built to run where people actually are.
Tiny Aya delivers strong multilingual performance in 70+ global languages in a 3.35B parameter model, efficient enough to run locally, even on a phone.
RT @Cohere_Labs: Introducing ✨Tiny Aya✨, a family of massively multilingual small language models built to run where people actually are.
Tiny Aya delivers strong multilingual performance in 70+ global languages in a 3.35B parameter model, efficient enough to run locally, even on a phone.
Post #2312
1.24K
Hugging Face (Twitter)
RT @Cohere_Labs: Very special to work with our @huggingface friends to bring Tiny Aya, the most capable multilingual open-weight model at its scale to the world! 🚀
Big thanks to @ngxson for the huge help merging the changes into llama.cpp.
RT @Cohere_Labs: Very special to work with our @huggingface friends to bring Tiny Aya, the most capable multilingual open-weight model at its scale to the world! 🚀
Big thanks to @ngxson for the huge help merging the changes into llama.cpp.
- 👍 1
Post #2311
1.02K
Hugging Face (Twitter)
RT @AdinaYakup: Happy Spring Festival🧧🐎
Here’s to another year of building and sharing!
新的一年，继续开源同行 🤗
RT @AdinaYakup: Happy Spring Festival🧧🐎
Here’s to another year of building and sharing!
新的一年，继续开源同行 🤗
- 🥰 1
Post #2310
741
Hugging Face (Twitter)
RT @NielsRogge: Dots.ocr is known for being among the SOTA for OCR
Looks like the new 1.5 model is SOTA on OlmOCRBench!
https://huggingface.co/rednote-hilab/dots.ocr-1.5
X (formerly Twitter) Niels Rogge (@NielsRogge) on X Dots.ocr is known for being among the SOTA for OCR
Looks like the new 1.5 model is SOTA on OlmOCRBench!
https://t.co/HwzeuKzzFD RT @NielsRogge: Dots.ocr is known for being among the SOTA for OCR
Looks like the new 1.5 model is SOTA on OlmOCRBench!
https://huggingface.co/rednote-hilab/dots.ocr-1.5
- 😁 1
Post #2309
606
Hugging Face (Twitter)
RT @Alibaba_Qwen: 🚀 Qwen3.5-397B-A17B is here: The first open-weight model in the Qwen3.5 series.
🖼️Native multimodal. Trained for real-world agents.
✨Powered by hybrid linear attention + sparse MoE and large-scale RL environment scaling.
⚡8.6x–19.0x decoding throughput vs Qwen3-Max
🌍201 languages & dialects
📜Apache2.0 licensed
🔗Dive in:
GitHub: github.com/QwenLM/Qwen3.5
Chat: chat.qwen.ai
API：https://modelstudio.console.alibabacloud.com/ap-southeast-1/?tab=doc#/doc/?type=model&url=2840914_2&modelId=group-qwen3.5-plus
Qwen Code: github.com/QwenLM/qwen-code
Hugging Face: https://huggingface.co/collections/Qwen/qwen35
ModelScope: https://modelscope.cn/collections/Qwen/Qwen35
blog: qwen.ai/blog?id=qwen3.5
RT @Alibaba_Qwen: 🚀 Qwen3.5-397B-A17B is here: The first open-weight model in the Qwen3.5 series.
🖼️Native multimodal. Trained for real-world agents.
✨Powered by hybrid linear attention + sparse MoE and large-scale RL environment scaling.
⚡8.6x–19.0x decoding throughput vs Qwen3-Max
🌍201 languages & dialects
📜Apache2.0 licensed
🔗Dive in:
GitHub: github.com/QwenLM/Qwen3.5
Chat: chat.qwen.ai
API：https://modelstudio.console.alibabacloud.com/ap-southeast-1/?tab=doc#/doc/?type=model&url=2840914_2&modelId=group-qwen3.5-plus
Qwen Code: github.com/QwenLM/qwen-code
Hugging Face: https://huggingface.co/collections/Qwen/qwen35
ModelScope: https://modelscope.cn/collections/Qwen/Qwen35
blog: qwen.ai/blog?id=qwen3.5
- 👀 1
Post #2308
455
Hugging Face (Twitter)
RT @RisingSayak: Will be there at the @OfficialINDIAai Impact Summit in Delhi from 17-19.
Will also present ReflectionFlow at the symposium on the 18th.
Kinda surprised there’s no real discussion about open science and open source, given the stellar speakers.
Anyway, looking forward to it!
RT @RisingSayak: Will be there at the @OfficialINDIAai Impact Summit in Delhi from 17-19.
Will also present ReflectionFlow at the symposium on the 18th.
Kinda surprised there’s no real discussion about open science and open source, given the stellar speakers.
Anyway, looking forward to it!
- ⚡ 1
- 👍 1
Post #2307
376
Hugging Face (Twitter)
RT @j_dekoninck: Introducing QED-Nano: a 4B model for mathematical proof writing, competitive with larger models like GPT-OSS-120B.
We open-source our entire pipeline, including data, code, and a blog post, hoping that the community can build on these artifacts to create more specialized models.
RT @j_dekoninck: Introducing QED-Nano: a 4B model for mathematical proof writing, competitive with larger models like GPT-OSS-120B.
We open-source our entire pipeline, including data, code, and a blog post, hoping that the community can build on these artifacts to create more specialized models.
- 😁 1
Post #2306
320
Hugging Face (Twitter)
RT @_lewtun: We trained a tiny 4B model to reason for millions of tokens through IMO-level problems.
Heaps excited to share our new blog post covering the full pipeline, from distilling the 🐳 to augmenting RL with a reasoning cache that unlocks extreme inference-time scaling for theorem proving.
https://huggingface.co/spaces/lm-provers/qed-nano-blogpost
RT @_lewtun: We trained a tiny 4B model to reason for millions of tokens through IMO-level problems.
Heaps excited to share our new blog post covering the full pipeline, from distilling the 🐳 to augmenting RL with a reasoning cache that unlocks extreme inference-time scaling for theorem proving.
https://huggingface.co/spaces/lm-provers/qed-nano-blogpost
- 👏 1
Post #2305
271
Hugging Face (Twitter)
RT @RisingSayak: An ambitious project today 🔥
We got an agent to write custom kernels that actually work for a given model, hardware instruction set, and other relevant model-dependent constraints.
Benchmarks are our rewards here 🤪
We got these kernels to work with Diffusers and `torch.compile` and they delivered ACTUAL SPEEDUP without messing up the quality 🏆
Despite the competitive landscape, we don't like to keep things private. Read all of it in the blog post below:
https://huggingface.co/blog/custom-cuda-kernels-agent-skills
RT @RisingSayak: An ambitious project today 🔥
We got an agent to write custom kernels that actually work for a given model, hardware instruction set, and other relevant model-dependent constraints.
Benchmarks are our rewards here 🤪
We got these kernels to work with Diffusers and `torch.compile` and they delivered ACTUAL SPEEDUP without messing up the quality 🏆
Despite the competitive landscape, we don't like to keep things private. Read all of it in the blog post below:
https://huggingface.co/blog/custom-cuda-kernels-agent-skills
Post #2304
224
Post #2303
261
Hugging Face (Twitter)
RT @turingcom: OpenEnv treats environments as first class infrastructure.
Through our collaboration with @AIatMeta and @huggingface, Turing is helping labs run tool-using agents against RL Environments that share:
-A standard step and reset API
-WebSocket sessions with per-client state
-MCP-style tool discovery and calling
-Observability hooks for rewards, errors, and drift
The payoff is simple. You can reuse the same evaluation pattern across domains and see where agents actually fail in long, tool-heavy workflows. Learn more below.
RT @turingcom: OpenEnv treats environments as first class infrastructure.
Through our collaboration with @AIatMeta and @huggingface, Turing is helping labs run tool-using agents against RL Environments that share:
-A standard step and reset API
-WebSocket sessions with per-client state
-MCP-style tool discovery and calling
-Observability hooks for rewards, errors, and drift
The payoff is simple. You can reuse the same evaluation pattern across domains and see where agents actually fail in long, tool-heavy workflows. Learn more below.
Post #2302
201
Hugging Face (Twitter)
RT @HuggingPapers: StepFun's Step 3.5 Flash
A sparse MoE model with 196B parameters, 11B active per token.
Achieves frontier-level reasoning comparable to GPT-5.2 xHigh and Gemini 3.0 Pro at 1/6th the decoding cost.
Ranks #1 on MathArena with 97.3% on AIME 2025.
RT @HuggingPapers: StepFun's Step 3.5 Flash
A sparse MoE model with 196B parameters, 11B active per token.
Achieves frontier-level reasoning comparable to GPT-5.2 xHigh and Gemini 3.0 Pro at 1/6th the decoding cost.
Ranks #1 on MathArena with 97.3% on AIME 2025.
Post #2301
347
Hugging Face (Twitter)
RT @vanstriendaniel: Data Designer from @nvidia now has full @huggingface Hub integration:
- load any dataset as a seed
- generate synthetic data,
- push results straight to the Hub
RT @vanstriendaniel: Data Designer from @nvidia now has full @huggingface Hub integration:
- load any dataset as a seed
- generate synthetic data,
- push results straight to the Hub
Post #2300
453
Hugging Face (Twitter)
RT @andimarafioti: 30x real-time speech-to-text in your browser.
No installs. No servers.
Just open the website.
RT @andimarafioti: 30x real-time speech-to-text in your browser.
No installs. No servers.
Just open the website.
Post #2299
278
Hugging Face (Twitter)
RT @Xianbao_QIAN: Pony Alpha is open sourced finally. Welcome GLM 5 by @Zai_org on @huggingface !
- 744B parameters (40B active)
- 28.5T pretrain tokens
- DeepSeek Sparse Attention (DSA)
- Trained by asynchronous RL infrastructure slime
- MIT license
- Native FP8 version available
huggingface.co/zai-org/GLM-5
RT @Xianbao_QIAN: Pony Alpha is open sourced finally. Welcome GLM 5 by @Zai_org on @huggingface !
- 744B parameters (40B active)
- 28.5T pretrain tokens
- DeepSeek Sparse Attention (DSA)
- Trained by asynchronous RL infrastructure slime
- MIT license
- Native FP8 version available
huggingface.co/zai-org/GLM-5
Post #2298
148
Hugging Face (Twitter)
RT @lvwerra: Public benchmarks lag behind what frontier labs are using internally to test and develop LLMs, yet they are the key driver of progress for LLMs.
This needs to change!
Excited to work with @SnorkelAI who are investing $3M do build out the evaluation ecosystem with the community.
RT @lvwerra: Public benchmarks lag behind what frontier labs are using internally to test and develop LLMs, yet they are the key driver of progress for LLMs.
This needs to change!
Excited to work with @SnorkelAI who are investing $3M do build out the evaluation ecosystem with the community.
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