Hugging Face Changelog
MCP Server Enhancements
โข 111
Lucas Silva PRO
YuLexuan30
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upvoted a changelog 4 days ago
MCP Server Enhancements reacted to SeaWolf-AI's post with ๐ 8 days ago
A small gift for anyone building or studying foundation models.
Most "open" models hand you the weights and stop there. With Aether-7B-5Attn we wanted to hand over the whole thing โ so you can actually learn from it, reproduce it, and build on it: the data recipe, the training code, every hyperparameter, the complete logs, and the intermediate checkpoints. All Apache-2.0, reproducible byte-for-byte.
What you can do with it:
๐ Rebuild it from scratch, or fork the recipe for your own model
๐ฌ Study a real heterogeneous-attention MoE โ 49 layers place 5 attention mechanisms on a 7ร7 Latin square, arranged as a clean, attributable ablation
๐ Trace training dynamics across the released checkpoints (110k / 115k / 162k)
It's a modest 6.59B model, and an honest one โ the limitations (no KV-cache in this build, small scale) are written right in the card. We're not claiming it's special. If any piece of it saves you time or teaches you something, that's exactly what we hoped for. ๐ค
๐ Full write-up โ
[blog] ยท https://huggingface.co/blog/FINAL-Bench/opensource-llm
๐ฆ 5 Attention Base ยท https://huggingface.co/FINAL-Bench/Aether-7B-5Attn
๐ฏ 5 Attention Instruct ยท https://huggingface.co/FINAL-Bench/Aether-7B-5Attn-it
๐ 5 Attention Live demo ยท https://huggingface.co/spaces/FINAL-Bench/Aether-Sovereign-AI
๐ฆ 7 Attention Base ยท https://huggingface.co/FINAL-Bench/Aether-7B-7Attn-base
๐ฆ 11 Attention Base ยท https://huggingface.co/FINAL-Bench/Aether-6B-11Attn-base
๐งฌ Collection ยท https://huggingface.co/collections/FINAL-Bench/aether-foundation-model
#opensource #LLM #MoE #reproducibility #Apache2 reacted to danielhanchen's post with ๐ 8 days ago
Gemma 4 is now faster and much more accurate! ๐
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4Organizations
upvoted a changelog 4 days ago
reacted to SeaWolf-AI's post with ๐ 8 days ago
Post
5130
A small gift for anyone building or studying foundation models.
Most "open" models hand you the weights and stop there. With Aether-7B-5Attn we wanted to hand over the whole thing โ so you can actually learn from it, reproduce it, and build on it: the data recipe, the training code, every hyperparameter, the complete logs, and the intermediate checkpoints. All Apache-2.0, reproducible byte-for-byte.
What you can do with it:
๐ Rebuild it from scratch, or fork the recipe for your own model
๐ฌ Study a real heterogeneous-attention MoE โ 49 layers place 5 attention mechanisms on a 7ร7 Latin square, arranged as a clean, attributable ablation
๐ Trace training dynamics across the released checkpoints (110k / 115k / 162k)
It's a modest 6.59B model, and an honest one โ the limitations (no KV-cache in this build, small scale) are written right in the card. We're not claiming it's special. If any piece of it saves you time or teaches you something, that's exactly what we hoped for. ๐ค
๐ Full write-up โ
[blog] ยท https://huggingface.co/blog/FINAL-Bench/opensource-llm
๐ฆ 5 Attention Base ยท FINAL-Bench/Aether-7B-5Attn
๐ฏ 5 Attention Instruct ยท FINAL-Bench/Aether-7B-5Attn-it
๐ 5 Attention Live demo ยท FINAL-Bench/Aether-Sovereign-AI
๐ฆ 7 Attention Base ยท https://huggingface.co/FINAL-Bench/Aether-7B-7Attn-base
๐ฆ 11 Attention Base ยท FINAL-Bench/Aether-6B-11Attn-base
๐งฌ Collection ยท https://huggingface.co/collections/FINAL-Bench/aether-foundation-model
#opensource #LLM #MoE #reproducibility #Apache2
Most "open" models hand you the weights and stop there. With Aether-7B-5Attn we wanted to hand over the whole thing โ so you can actually learn from it, reproduce it, and build on it: the data recipe, the training code, every hyperparameter, the complete logs, and the intermediate checkpoints. All Apache-2.0, reproducible byte-for-byte.
What you can do with it:
๐ Rebuild it from scratch, or fork the recipe for your own model
๐ฌ Study a real heterogeneous-attention MoE โ 49 layers place 5 attention mechanisms on a 7ร7 Latin square, arranged as a clean, attributable ablation
๐ Trace training dynamics across the released checkpoints (110k / 115k / 162k)
It's a modest 6.59B model, and an honest one โ the limitations (no KV-cache in this build, small scale) are written right in the card. We're not claiming it's special. If any piece of it saves you time or teaches you something, that's exactly what we hoped for. ๐ค
๐ Full write-up โ
[blog] ยท https://huggingface.co/blog/FINAL-Bench/opensource-llm
๐ฆ 5 Attention Base ยท FINAL-Bench/Aether-7B-5Attn
๐ฏ 5 Attention Instruct ยท FINAL-Bench/Aether-7B-5Attn-it
๐ 5 Attention Live demo ยท FINAL-Bench/Aether-Sovereign-AI
๐ฆ 7 Attention Base ยท https://huggingface.co/FINAL-Bench/Aether-7B-7Attn-base
๐ฆ 11 Attention Base ยท FINAL-Bench/Aether-6B-11Attn-base
๐งฌ Collection ยท https://huggingface.co/collections/FINAL-Bench/aether-foundation-model
#opensource #LLM #MoE #reproducibility #Apache2
- 5 replies
reacted to danielhanchen's post with ๐ 8 days ago
Post
5576
Gemma 4 is now faster and much more accurate! ๐
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
- 8 replies
upvoted a changelog 13 days ago
Hugging Face Changelog
Filter Models page by Hardware
โข 217
Please add GGUF options
#3 opened about 1 month ago
by YuLexuan30
updated a
model about 1 month ago
published a
model about 1 month ago
liked a
Space about 1 month ago
reacted to AxionLab-official's post with ๐ฅ about 1 month ago
Post
8561
Please, give a follow to SupraLabs!
We are researching the most, just to make the best medium models FOR YOU!
SupraLabs/Supra-A2A-Nano-Exp
SupraLabs/Supra-1.5-50M-Instruct-exp
SupraLabs/Supra-50M-Reasoning
SupraLabs/supra-title-50M-pre-gguf
Check more at Supralabs org!
SupraLabs
---
@LH-Tech-AI
@QyrouNnet-AI
@LyJonathan
@Mmorgan-ML
@User01110
We are researching the most, just to make the best medium models FOR YOU!
SupraLabs/Supra-A2A-Nano-Exp
SupraLabs/Supra-1.5-50M-Instruct-exp
SupraLabs/Supra-50M-Reasoning
SupraLabs/supra-title-50M-pre-gguf
Check more at Supralabs org!
---
@LH-Tech-AI
@QyrouNnet-AI
@LyJonathan
@Mmorgan-ML
@User01110
- 2 replies
Add larger resolution options
#18 opened about 1 month ago
by YuLexuan30
updated a
Space about 1 month ago
liked a
Space about 1 month ago
About the character sheet
3
#18 opened about 1 month ago
by 
kus
Portrait Mode?
1
#19 opened about 1 month ago
by 
davoodkharmanzar
Rio-3.5-Open-397B โ 0.6 x Nex-N2_pro + 0.4 x Qwen
๐ค๐ 16
15
#18 opened about 1 month ago
by 
spanspek
30 min of ZeroGPU gone
๐๐ 2
3
#2 opened about 2 months ago
by 
Daankular
Thank you for this, most closed models can't do it
2
#17 opened about 1 month ago
by YuLexuan30
reacted to sergiopaniego's post with ๐ฅ about 2 months ago
Post
3960
OpenEnv has a new home: github.com/huggingface/OpenEnv
Starting today, it's coordinated by a committee that includes Meta-PyTorch, Reflection, Unsloth, Modal, Prime Intellect, Nvidia, Mercor, Fleet AI, and Hugging Face
frontier labs train their models and their harnesses together. Claude knows Claude Code. GPT-5.5 knows Codex. that's not an accident, it's training. open-source models deserve the same magic, but pulling that off requires infrastructure that belongs to everyone, not one lab
OpenEnv is that layer. one api, any harness, any trainer, any environment
Rewards and training loops stay in TRL, Unsloth, wherever you already work. OpenEnv is the socket they all plug into
Get involved!
Full announcement: https://huggingface.co/blog/openenv-agentic-rl
Starting today, it's coordinated by a committee that includes Meta-PyTorch, Reflection, Unsloth, Modal, Prime Intellect, Nvidia, Mercor, Fleet AI, and Hugging Face
frontier labs train their models and their harnesses together. Claude knows Claude Code. GPT-5.5 knows Codex. that's not an accident, it's training. open-source models deserve the same magic, but pulling that off requires infrastructure that belongs to everyone, not one lab
OpenEnv is that layer. one api, any harness, any trainer, any environment
Rewards and training loops stay in TRL, Unsloth, wherever you already work. OpenEnv is the socket they all plug into
Get involved!
Full announcement: https://huggingface.co/blog/openenv-agentic-rl
reacted to AxionLab-official's post with ๐ about 2 months ago
Post
10997
THIS IS CRAZY! THE MODEL ON THE IMAGE(Supra-50M-Reasoning) answered correctly and its QUANTIZED IN 2BIT! THE RESPONSE IS CORRECT, IN A 15MB SIZE FILE!
- 14 replies
upvoted a changelog about 2 months ago
Hugging Face Changelog
Filter Models page by Base Models only
โข 184