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prithivMLmods 
posted an update 8 days ago
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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. 👇

🔗 Qwen3.6-MoE: https://huggingface.co/collections/prithivMLmods/qwen36-35b-a3b-compressions
🔗 Qwen3.6-27B Compressions: https://huggingface.co/collections/prithivMLmods/qwen36-27b-compressions

🤗 > To learn more, visit the app page or the respective model pages.
prithivMLmods 
posted an update 13 days ago
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HY-World-2.0 — 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

🤗To learn more, visit the app page or the respective model pages.
sergiopaniego 
posted an update 15 days ago
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Earlier this month, Apple introduced Simple Self-Distillation: a fine-tuning method that improves models on coding tasks just by sampling from the model and training on its own outputs with plain cross-entropy

And… it's already supported in TRL, built by Kashif Rasul. you can really feel the pace of development in the team 🐎

Paper by Ruixiang ZHANG, He Bai, Huangjie Zheng, Navdeep Jaitly, Ronan Collobert, Yizhe Zhang at Apple 🍎

How it works: the model generates completions at a training-time temperature (T_train) with top_k/top_p truncation, then fine-tunes on them with plain cross-entropy. no labels or verifier needed

You can try it right away with this ready-to-run example (Qwen3-4B on rStar-Coder):
https://github.com/huggingface/trl/blob/main/trl/experimental/ssd/ssd.py
or benchmark a checkpoint with the eval script:
https://github.com/huggingface/trl/blob/main/trl/experimental/ssd/ssd_eval.py

One neat insight from the paper: T_train and T_eval compose into an effective T_eff = T_train × T_eval, so a broad band of configs works well. even very noisy samples still help

Want to dig deeper?

Paper: Embarrassingly Simple Self-Distillation Improves Code Generation (2604.01193)
Trainer docs: https://huggingface.co/docs/trl/main/en/ssd_trainer
sdiazlor 
posted an update 15 days ago
Aurelien-Morgan 
posted an update 17 days ago
prithivMLmods 
posted an update 18 days ago
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A new comparator on Spaces showcases Standard FLUX.2 Decoder vs. FLUX.2 Small Decoder. The Small Decoder is ~1.4× faster, uses ~1.4× less VRAM, and maintains near-identical image quality. It has ~28M parameters with narrower channels [96, 192, 384, 384] vs. [128, 256, 512, 512], and the demo supports sequence generation by running both decoders simultaneously and comparing the results side by side.

🤗 Comparator: prithivMLmods/Flux.2-4B-Decoder-Comparator
🔗 FLUX.2-small-decoder: black-forest-labs/FLUX.2-small-decoder
🔗 GitHub: https://github.com/PRITHIVSAKTHIUR/Flux.2-4B-Encoder-Comparator
🚁 Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

🤗 > App built on the Gradio SDK. To learn more, visit the app page or the respective model pages.
prithivMLmods 
posted an update 19 days ago
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Now, a collection of various compression schemes for Gemma 4 and the abliterated version 1 of dense models is available on the Hub. Check it out via the links below. 👇

🔗Gemma 4 Compression(s)- https://huggingface.co/collections/prithivMLmods/gemma-4-compressions
🔗Gemma 4 Uncensored [MAX] + Compression(s) - [`β ]- https://huggingface.co/collections/prithivMLmods/gemma-4-uncensored-max-compressions
🔗Gemma 4 Compression(s) - MoE- https://huggingface.co/collections/prithivMLmods/gemma-4-compressions-moe
🔗Gemma-4 F32 GGUF- https://huggingface.co/collections/prithivMLmods/gemma-4-f32-gguf

🤗 > To learn more, visit the app page or the respective model pages.
sergiopaniego 
posted an update 21 days ago
prithivMLmods 
posted an update 22 days ago
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Now the demo for image detection based on SAM3 and Gemma-4 (*Filter) is available on Spaces, using full-fledged Transformers inference with multimodal reasoning for processed images. It also supports video segmentation (mask), video segmentation (annotation), and image click segmentation.

🤗 Demo Space: prithivMLmods/SAM3-Gemma4-CUDA
🥽 SAM3: facebook/sam3
🔗 gemma-4-E2B-it: google/gemma-4-E2B-it

To learn more, visit the app page or the respective model pages.
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prithivMLmods 
posted an update 25 days ago
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The demo for Image Detection (*Filter) based on SAM3 and Qwen-3.5 is now available on Hugging Face Spaces using Transformers inference, with multimodal reasoning for processed images, and it also supports video segmentation (mask), video segmentation (annotation), and image click segmentation.

🤗 Demo Space: prithivMLmods/SAM3-Plus-Qwen3.5
🥽 SAM3: facebook/sam3
🔗 Qwen-3.5: Qwen/Qwen3.5-2B

To learn more, visit the app page or the respective model pages.
  • 5 replies
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Shrijanagain 
posted an update 26 days ago
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sKT-Ai-Labs


Join fast we will soon published tokens and all join and get started because we will soon off join request button if you want you can join fast guys
  • 1 reply
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sergiopaniego 
posted an update 28 days ago
sergiopaniego 
posted an update about 1 month ago
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TRL is officially an adult 🥳

excited to announce TRL v1.0❗️

head to the blog to see how we got here and what’s next for this post-training library, designed to keep pace with the field

https://huggingface.co/blog/trl-v1
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sdiazlor 
posted an update about 1 month ago
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Pruna OSS is turning 1! To mark this milestone, we're launching the First Prune initiative.

What's First Prune:
If you contribute to open issues at our GitHub repo, you earn Pruna Inference API credits.

How you can participate:
• Pick an open issue labelled "first-prune" and assign it to you
• Submit your PR and mark it ready for review by April 30
• Find out more in the PR template when you open a PR

Each merged PR scores 30 credits.

Let’s build something great together! Find your issue: https://github.com/PrunaAI/pruna/issues
Shrijanagain 
posted an update about 1 month ago
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​🚀 Bharat AI Revolution ka Hissa Banein! 🇮🇳

​Kya aap Bharat ko AI ki duniya mein ek nayi pehchan dilana chahte hain ?

SKT AI Labs sirf ek naam nahi, ek mission hai—desh ko digital shakti dene ka aur "Viksit Bharat" ke sapne ko sach karne ka.

​Humse Kyun Judein?

​1. Desh ka Apna AI: Hum aise models bana rahe hain jo khas taur par Bharat ki zarooraton aur bhashaon ke liye hain.

​2. Open Collaboration: Hamare Hugging Face repository par hamare kaam ko dekhein, test karein aur apna yogdan dein.

3. Technological Growth: Agar aap student hain, developer hain ya tech enthusiast hain, toh hamare saath naya seekhne aur grow karne ka yeh behtareen mauka hai.

​Join here

sKT-Ai-Labs

🔗
sKT-Ai-Labs


​Aaiye, saath milkar Bharat AI Revolution ko aage badhate hain! 💻🔥

​#SKTAILabs #DigitalIndia #AIRevolution #ViksitBharat #TechInnovation #JoinTheMission
Shrijanagain 
posted an update about 1 month ago
prithivMLmods 
posted an update about 1 month ago
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Flux-Klein-KV-Edit-Consistency demo is now available on Spaces. It preserves character identity and delivers high-quality, realistic results after edits. No need for any special prompts, just upload the image, type your prompt, and get the resulting image blazing fast.

🔥 Demo Space: prithivMLmods/flux-klein-kv-edit-consistency
🤗 Model: black-forest-labs/FLUX.2-klein-9b-kv
🤗 Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
🔗 Gradio Server Mode: https://www.gradio.app/main/guides/server-mode

➔ Built with Headless Gradio, an alternative to using gr.Blocks for creating the frontend and triggering events, powered by FastAPI + Gradio. You can now design the frontend however you want, with continued support for APIs, MCP, and ZeroGPU.

➔ Gradio Server Mode is now available from gradio@v6.10.0.

To learn more, visit the app page or the respective model pages.
Shrijanagain 
posted an update about 1 month ago
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​We are thrilled to announce the launch of SKT-OMNI-CORPUS-146T-V1, a massive-scale, high-quality dataset designed to power the next generation of Foundation Models (LLMs) from scratch.
​Developed at SKT AI LABS, this corpus is not just a collection of data; it’s a mission to decentralize high-grade AI training for regional languages and global knowledge.

​💎 Key Highlights:

​•• Massive Scale: Targeting a multi-terabyte architecture for 146T-level tokenization.

•• ​Pure Quality: Curated from 500+ Elite Sources

•• ​Structured for MoE: Perfectly sharded into 3.5GB standardized units (SKT-𝕻 series) for seamless distributed training.

​🤝 Open for Collaboration!

​We are looking for AI researchers, CUDA engineers, and data scientists to join us in this journey of building Project Surya and the ST-X Series models. Whether it's optimization, custom tokenization, or architecture design—let’s build the future together.

​Explore the Dataset on Hugging Face:

🔗 https://huggingface.co/datasets/Shrijanagain/SKT-OMNI-CORPUS-146T-V1

DSR -- 🔗 https://huggingface.co/datasets/Shrijanagain/SKT-DSRx10000

​#AI #MachineLearning #OpenSource #IndicAI #SKTAILABS #LLM #BigData #HuggingFace #InnovationIndia
prithivMLmods 
posted an update about 1 month ago
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Map-Anything v1 (Universal Feed-Forward Metric 3D Reconstruction) demo is now available on Hugging Face Spaces. Built with Gradio and integrated with Rerun, it performs multi-image and video-based 3D reconstruction, depth, normal map, and interactive measurements.

🤗 Demo: prithivMLmods/Map-Anything-v1
🤗 Model: facebook/map-anything-v1
🤗 Hf-Papers: MapAnything: Universal Feed-Forward Metric 3D Reconstruction (2509.13414)