minimax h3 turbo + lora's
🎬
77
Video generation with a synchronized soundtrack
Lucas Silva PRO
YuLexuan30
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liked a Space 1 day ago
observantdistressed/minimax-h3-turbo reacted to yanghaojin's post with 🚀 12 days ago
Fish Audio’s Drama 3 text-to-speech now runs locally on Apple silicon and DGX Spark with gbx-lm. 🎙️
https://huggingface.co/GreenBitAI/Drama-3-8bit-paged
Real time on 64 GB Macs and up (2.6x), and it still runs on a 48 GB MacBook Pro: experts stream from the SSD
Zero-shot voice cloning from a 5–30 s clip, and the cloned voice can speak other languages
Multi-speaker dialogue, cues like [laughs] [whispering], 83 languages
OpenAI-compatible /v1/audio/speech with streaming, no PyTorch needed
Built with Fish Audio · community build · Fish Audio Community License updated a model 17 days ago
YuLexuan30/balloonblowtopoph3Organizations
liked a
Space 1 day ago
reacted to yanghaojin's post with 🚀 12 days ago
Post
2,812
Fish Audio’s Drama 3 text-to-speech now runs locally on Apple silicon and DGX Spark with gbx-lm. 🎙️
GreenBitAI/Drama-3-8bit-paged
Real time on 64 GB Macs and up (2.6x), and it still runs on a 48 GB MacBook Pro: experts stream from the SSD
Zero-shot voice cloning from a 5–30 s clip, and the cloned voice can speak other languages
Multi-speaker dialogue, cues like [laughs] [whispering], 83 languages
OpenAI-compatible /v1/audio/speech with streaming, no PyTorch needed
Built with Fish Audio · community build · Fish Audio Community License
GreenBitAI/Drama-3-8bit-paged
Real time on 64 GB Macs and up (2.6x), and it still runs on a 48 GB MacBook Pro: experts stream from the SSD
Zero-shot voice cloning from a 5–30 s clip, and the cloned voice can speak other languages
Multi-speaker dialogue, cues like [laughs] [whispering], 83 languages
OpenAI-compatible /v1/audio/speech with streaming, no PyTorch needed
Built with Fish Audio · community build · Fish Audio Community License
updated a
model 17 days ago
published a
model 18 days ago
liked a
model 19 days ago
reacted to Banaxi-Tech's post with 🔥 19 days ago
Post
4,249
Hi everyone
We at
saicr have found a very interesting "thing" we call ADN via interpretabillity. It appears on EVERY prompt sent to the model. More on that later.
Also I made a X account follow it for more updates:
@banaxitech
And KleinML:
@kleinmlai
Here's my website for Klein ML: https://kleinml.com/?ref=huggingface.co
We at
Also I made a X account follow it for more updates:
@banaxitech
And KleinML:
@kleinmlai
Here's my website for Klein ML: https://kleinml.com/?ref=huggingface.co
- 4 replies
Example workflow?
7
#1 opened 21 days ago
by YuLexuan30
sorry but this is best trash model😭🙏
👍 13
31
#8 opened 26 days ago
by 
darkenHUB
DISTILLED versus BASE: 8MP comparison
11
#25 opened 25 days ago
by 
Liquidmind111
reacted to mithulaartigala's post with 🔥 30 days ago
Post
4,647
I am LOVING HuggingFace Pro <3
- 7 replies
reacted to Parveshiiii's post with 🤗 about 1 month ago
Post
3,855
Most deepfake audio detectors are quietly cheating.
They don’t really listen to the speech — they just look at how long the embedding vector is. Once they figure that out, accuracy looks great on paper and falls apart in the wild.
AIRealNet-Audio was built to stop that shortcut.
It forces every feature onto the unit hypersphere (twice) so the model can only use direction, not magnitude. Trained on speech from 100+ different TTS and voice-cloning systems, plus real human recordings under heavy compression and noise.
The result is a detector that actually has to learn the artifacts instead of gaming the feature space.
Model: Modotte/AIRealNet-Audio
They don’t really listen to the speech — they just look at how long the embedding vector is. Once they figure that out, accuracy looks great on paper and falls apart in the wild.
AIRealNet-Audio was built to stop that shortcut.
It forces every feature onto the unit hypersphere (twice) so the model can only use direction, not magnitude. Trained on speech from 100+ different TTS and voice-cloning systems, plus real human recordings under heavy compression and noise.
The result is a detector that actually has to learn the artifacts instead of gaming the feature space.
Model: Modotte/AIRealNet-Audio
liked a
Space about 2 months ago
Any chance for a bigger text encoder (e.g. Gemma 4 26b) for the next version?
👍 2
22
#62 opened 3 months ago
by 
kabachuha
liked a
model 3 months ago
I'm not getting any speedup from int8 convrot on my 5-series card. Has anyone tried this?
9
#75 opened 3 months ago
by 
liuxingsyue
upvoted a changelog 4 months ago
Hugging Face Changelog
MCP Server Enhancements
• 253
reacted to SeaWolf-AI's post with 🚀 4 months ago
Post
5,164
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 — 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:
🔁 Rebuild it from scratch, or fork the recipe for your own model
🔬 Study a real heterogeneous-attention MoE — 49 layers place 5 attention mechanisms on a 7×7 Latin square, arranged as a clean, attributable ablation
📈 Trace training dynamics across the released checkpoints (110k / 115k / 162k)
It's a modest 6.59B model, and an honest one — 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. 🤗
📖 Full write-up →
[blog] · https://huggingface.co/blog/FINAL-Bench/opensource-llm
📦 5 Attention Base · FINAL-Bench/Aether-7B-5Attn
🎯 5 Attention Instruct · FINAL-Bench/Aether-7B-5Attn-it
🚀 5 Attention Live demo · FINAL-Bench/Aether-Sovereign-AI
📦 7 Attention Base · https://huggingface.co/FINAL-Bench/Aether-7B-7Attn-base
📦 11 Attention Base · FINAL-Bench/Aether-6B-11Attn-base
🧬 Collection · 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 — 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:
🔁 Rebuild it from scratch, or fork the recipe for your own model
🔬 Study a real heterogeneous-attention MoE — 49 layers place 5 attention mechanisms on a 7×7 Latin square, arranged as a clean, attributable ablation
📈 Trace training dynamics across the released checkpoints (110k / 115k / 162k)
It's a modest 6.59B model, and an honest one — 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. 🤗
📖 Full write-up →
[blog] · https://huggingface.co/blog/FINAL-Bench/opensource-llm
📦 5 Attention Base · FINAL-Bench/Aether-7B-5Attn
🎯 5 Attention Instruct · FINAL-Bench/Aether-7B-5Attn-it
🚀 5 Attention Live demo · FINAL-Bench/Aether-Sovereign-AI
📦 7 Attention Base · https://huggingface.co/FINAL-Bench/Aether-7B-7Attn-base
📦 11 Attention Base · FINAL-Bench/Aether-6B-11Attn-base
🧬 Collection · https://huggingface.co/collections/FINAL-Bench/aether-foundation-model
#opensource #LLM #MoE #reproducibility #Apache2
- 5 replies
reacted to danielhanchen's post with 🚀 4 months ago
Post
6,998
Gemma 4 is now faster and much more accurate! 🚀
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 4 months ago
Hugging Face Changelog
Filter Models page by Hardware
• 230
Please add GGUF options
#3 opened 5 months ago
by YuLexuan30