ARCHead: Activation-Metric Residual Correction for Large Language Model Output Heads
Paper β’ 2608.02703 β’ Published β’ 6
open/ acc
community
AI & ML interests
None defined yet.
Q-bertΒ
authored a
paper 3 days ago
prithivMLmodsΒ
posted an update 9 days ago
Post
4117
Made a demo for Text/Image-to-3D Video and Image-to-3D Video asset generation using TRELLIS.2. It is paired with Z-Image-Turbo to accelerate the input image preprocessing pipeline, streamlining the Image-to-3D workflow. The generated GLB (GL Transmission Format) files are converted into MP4 (MPEG-4) videos, making them easy to preview and share. Try it now on Hugging Face Spaces.π€
β Image-to-3D-Video-Asset-Generator: prithivMLmods/Image-to-3D-Video-Asset-Generator
β collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
β github: https://github.com/PRITHIVSAKTHIUR/Image-to-3D-Video-Asset-Generator
β€· To learn more, visit the app page or the respective model pages.
β Image-to-3D-Video-Asset-Generator: prithivMLmods/Image-to-3D-Video-Asset-Generator
β collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
β github: https://github.com/PRITHIVSAKTHIUR/Image-to-3D-Video-Asset-Generator
β€· To learn more, visit the app page or the respective model pages.
prithivMLmodsΒ
posted an update about 2 months ago
Post
7909
Wan2.2-I2V-Fast with highly upscaled sequential frame sampling is now available as a Spaces demo, built using Wan2.2-I2V and FLUX.2-Klein. Try the demo using the links below.π
β wan2.2-i2v-fast : https://huggingface.co/spaces/prithivMLmods/wan2.2-i2v-fast
β github: https://github.com/prithivsakthiur/wan2.2-i2v-fast
β collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
β€· To learn more, visit the app page or the respective model pages.
β wan2.2-i2v-fast : https://huggingface.co/spaces/prithivMLmods/wan2.2-i2v-fast
β github: https://github.com/prithivsakthiur/wan2.2-i2v-fast
β collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
β€· To learn more, visit the app page or the respective model pages.
cfahlgren1Β
submitted a
paper to Daily Papers about 2 months ago
prithivMLmodsΒ
posted an update 2 months ago
Post
2270
Dropping the collection of Qwen 3.5/3.6 MTP GGUF quants. π€
π Collection 1: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-moe-stable
π Collection 2: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-stable
> To learn more, visit the respective model pages.
π Collection 1: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-moe-stable
π Collection 2: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-stable
> To learn more, visit the respective model pages.
prithivMLmodsΒ
posted an update 2 months ago
Post
6301
PiD β Pixel Diffusion Decoder Image Edit Upscale and Image Generation Upscale, an all-in-one demo, is now live on Spaces! Great improvements in realism-based image generation and editing are powered by FLUX.2-Klein, while image generation is paired with Z-Image, and upscaling is enabled by default!
π€ Space: prithivMLmods/PiD-Image-Upscaler
π Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
π€ > To learn more, visit the app page or the respective model pages.
π€ Space: prithivMLmods/PiD-Image-Upscaler
π Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
π€ > To learn more, visit the app page or the respective model pages.
gigantΒ
authored a
paper 3 months ago
prithivMLmodsΒ
posted an update 3 months ago
Post
5626
I've made 8 Spaces in the Qwen-Image-Edit series, and out of them, 5 Spaces reached βSpace of the Weekβ! A few Spaces are still topping the list even after many months.
Cumulatively, the series has crossed 8.2 million+ ZeroGPU runs and nearly 4 million visitors overall.
Thanks for all the community support! π€β€οΈ
π Spaces: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
Cumulatively, the series has crossed 8.2 million+ ZeroGPU runs and nearly 4 million visitors overall.
Thanks for all the community support! π€β€οΈ
π Spaces: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
- 4 replies
gigantΒ
submitted a
paper to Daily Papers 3 months ago
Post
3167
ππ»ββοΈ Hey there folks ,
Turns out : if we predict π earth we can save a lot of time looking for interesting things and less time looking at things that we expect to see.
Sentinel-2 imagery π°οΈbasically takes a long time to download towards earth. so our "near real time" systems are quite far from that in practical terms.
meanwhile , if we "predict" what we will see , based on what we do see , we can send down much less data in a timely way , and prioritize π‘earth-bound response .
I'm talking about illegal fishing , logging , mining or building in nature reserves , the more of that we predict early the more we're able to stop it on time.
At least that's the concept !
check out the blog : https://huggingface.co/blog/Tonic/save-patagonia-by-predicting-earth
- Collection: https://huggingface.co/collections/NuTonic/earth-observation-with-temporal-and-general-understanding
- Code: https://github.com/Josephrp/Nutonic
- Dataset: NuTonic/sat-vl-sft-training-ready-v1
- Model: NuTonic/lspace
- Training: NuTonic/lspace-trackio
- Evals: NuTonic/Patagonia_Eval
Turns out : if we predict π earth we can save a lot of time looking for interesting things and less time looking at things that we expect to see.
Sentinel-2 imagery π°οΈbasically takes a long time to download towards earth. so our "near real time" systems are quite far from that in practical terms.
meanwhile , if we "predict" what we will see , based on what we do see , we can send down much less data in a timely way , and prioritize π‘earth-bound response .
I'm talking about illegal fishing , logging , mining or building in nature reserves , the more of that we predict early the more we're able to stop it on time.
At least that's the concept !
check out the blog : https://huggingface.co/blog/Tonic/save-patagonia-by-predicting-earth
- Collection: https://huggingface.co/collections/NuTonic/earth-observation-with-temporal-and-general-understanding
- Code: https://github.com/Josephrp/Nutonic
- Dataset: NuTonic/sat-vl-sft-training-ready-v1
- Model: NuTonic/lspace
- Training: NuTonic/lspace-trackio
- Evals: NuTonic/Patagonia_Eval
- 2 replies
gigantΒ
authored a
paper 3 months ago
Post
2898
I'm releasing OpenCS2 a 11TB dataset of around 5000 hours of counter strike gameplay recording.
- HD resolution - 1280Γ720 Β· 32 fps
- For each frame keyboard and mouse + world state (player position, velocity, weapon ...)
- HD Stereo audio
- All 10 players perspective
https://huggingface.co/collections/blanchon/opencs2
- HD resolution - 1280Γ720 Β· 32 fps
- For each frame keyboard and mouse + world state (player position, velocity, weapon ...)
- HD Stereo audio
- All 10 players perspective
https://huggingface.co/collections/blanchon/opencs2
- 1 reply
Aurelien-MorganΒ
posted an update 3 months ago
Post
1106
@retrain-pipelines v0.2.0 is out !
I'm at Station F at My booth with GOSIM Paris 2026 today & tomorrow.
Come meet me for a live in-person demo and a chat !
I'm at Station F at My booth with GOSIM Paris 2026 today & tomorrow.
Come meet me for a live in-person demo and a chat !
- 1 reply
prithivMLmodsΒ
posted an update 3 months ago
Post
5964
Multimodal-Edge Demo, a node-based inference canvas demo, is now live on Spaces. It features node-based Transformers for fast inference across 10+ edge-device multimodal models on the Hub, all within a single space. The series includes models from Qwen3.5, Qwen3-VL, Gemma 4, and the LFM 2.5 VL model series, with support for reasoning and grounding tasks.
π€ Demo: prithivMLmods/Multimodal-Edge-Node
π GitHub: https://github.com/PRITHIVSAKTHIUR/Multimodal-Edge-Node
β Multimodal Apps Collections: https://huggingface.co/collections/prithivMLmods/hall-of-multimodal-apps
π€ > To learn more, visit the app page or the respective model pages.
π€ Demo: prithivMLmods/Multimodal-Edge-Node
π GitHub: https://github.com/PRITHIVSAKTHIUR/Multimodal-Edge-Node
β Multimodal Apps Collections: https://huggingface.co/collections/prithivMLmods/hall-of-multimodal-apps
π€ > To learn more, visit the app page or the respective model pages.
Post
4406
ππ»ββοΈ Hey there folks,
since everyone liked my previous announcement post ( https://huggingface.co/posts/Tonic/338509028435394 ) so much , i'm back with more high quality proceedural datasets in the Geospacial domain for SFT training !
Check this one out :
NuTonic/sat-bbox-metadata-sft-v1
the goal is to be able to train vision models on multiple images for remote sensing analysis with one shot .
hope you like it ! π
since everyone liked my previous announcement post ( https://huggingface.co/posts/Tonic/338509028435394 ) so much , i'm back with more high quality proceedural datasets in the Geospacial domain for SFT training !
Check this one out :
NuTonic/sat-bbox-metadata-sft-v1
the goal is to be able to train vision models on multiple images for remote sensing analysis with one shot .
hope you like it ! π
- 2 replies
Post
3713
ππ»ββοΈ Hey there folks ,
I'm sharing huggingface's largest dataset of annotated statelite images today.
check it out here : NuTonic/sat-image-boundingbox-sft-full
I hope you like it , the idea is to be able to use this with small vision models π
I'm sharing huggingface's largest dataset of annotated statelite images today.
check it out here : NuTonic/sat-image-boundingbox-sft-full
I hope you like it , the idea is to be able to use this with small vision models π
prithivMLmodsΒ
posted an update 4 months ago
Post
1943
Now, a collection of various compression schemes for Qwen3.6 and the abliterated version 1 of dense models is available on the Hub. Check it out via the links below. π
π Qwen3.6-MoE: https://huggingface.co/collections/prithivMLmods/qwen36-35b-a3b-compressions
π Qwen3.6-27B Compressions: https://huggingface.co/collections/prithivMLmods/qwen36-27b-compressions
π€ > To learn more, visit the app page or the respective model pages.
π Qwen3.6-MoE: https://huggingface.co/collections/prithivMLmods/qwen36-35b-a3b-compressions
π Qwen3.6-27B Compressions: https://huggingface.co/collections/prithivMLmods/qwen36-27b-compressions
π€ > To learn more, visit the app page or the respective model pages.
Q-bertΒ
authored a
paper 4 months ago
IAMJBΒ
authored a
paper 4 months ago
prithivMLmodsΒ
posted an update 4 months ago
Post
4243
HY-World-2.0 β A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds is now available on Spaces, and it works both as native Gradio components and in Gradio server mode.
> HY-World-2.0-Demo: prithivMLmods/HY-World-2.0-Demo
> HY-World-2.0 [Server Mode]: prithivMLmods/HY-World-2.0-Demo
> Featuring 3D reconstruction and Gaussian splats with the Rerun viewer, along with camera poses, depth maps, and surface normals.
> In Server Mode, Gradio is served via FastAPI, with FastAPI remaining the top-level server.
> Model: tencent/HY-World-2.0
> GitHub: https://github.com/PRITHIVSAKTHIUR/HY-World-2.0-Demo
π€To learn more, visit the app page or the respective model pages.
> HY-World-2.0-Demo: prithivMLmods/HY-World-2.0-Demo
> HY-World-2.0 [Server Mode]: prithivMLmods/HY-World-2.0-Demo
> Featuring 3D reconstruction and Gaussian splats with the Rerun viewer, along with camera poses, depth maps, and surface normals.
> In Server Mode, Gradio is served via FastAPI, with FastAPI remaining the top-level server.
> Model: tencent/HY-World-2.0
> GitHub: https://github.com/PRITHIVSAKTHIUR/HY-World-2.0-Demo
π€To learn more, visit the app page or the respective model pages.