AI & ML interests

Fix issues and experiment with new things.

prithivMLmodsย 
posted an update about 1 month ago
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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.๐Ÿ‘‡

โž  wan2.2-i2v-fast : prithivMLmods/wan2.2-i2v-fast
โž  github: https://github.com/prithivsakthiur/wan2.2-i2v-fast
โž  collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

โคท To learn more, visit the app page or the respective model pages.
prithivMLmodsย 
posted an update about 2 months ago
prithivMLmodsย 
posted an update about 2 months ago
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PiD โ€” 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!

๐Ÿค— Space: prithivMLmods/PiD-Image-Upscaler
๐Ÿ”— Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

๐Ÿค— > To learn more, visit the app page or the respective model pages.
prithivMLmodsย 
posted an update about 2 months ago
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I've made 8 Spaces in the Qwen-Image-Edit series, and out of them, 5 Spaces reached โ€œSpace of the Weekโ€! 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! ๐Ÿค—โค๏ธ

๐Ÿ”— Spaces: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
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prithivMLmodsย 
posted an update 3 months ago
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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.

๐Ÿค— Demo: prithivMLmods/Multimodal-Edge-Node
๐Ÿ”— GitHub: https://github.com/PRITHIVSAKTHIUR/Multimodal-Edge-Node
โœ… Multimodal Apps Collections: https://huggingface.co/collections/prithivMLmods/hall-of-multimodal-apps

๐Ÿค— > To learn more, visit the app page or the respective model pages.
prithivMLmodsย 
posted an update 3 months 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. ๐Ÿ‘‡

๐Ÿ”— Qwen3.6-MoE: https://huggingface.co/collections/prithivMLmods/qwen36-35b-a3b-compressions
๐Ÿ”— Qwen3.6-27B Compressions: https://huggingface.co/collections/prithivMLmods/qwen36-27b-compressions

๐Ÿค— > To learn more, visit the app page or the respective model pages.
prithivMLmodsย 
posted an update 3 months ago
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HY-World-2.0 โ€” 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

๐Ÿค—To learn more, visit the app page or the respective model pages.
prithivMLmodsย 
posted an update 3 months ago
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A new comparator on Spaces showcases Standard FLUX.2 Decoder vs. FLUX.2 Small Decoder. The Small Decoder is ~1.4ร— faster, uses ~1.4ร— 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.

๐Ÿค— Comparator: https://huggingface.co/spaces/prithivMLmods/Flux.2-4B-Decoder-Comparator
๐Ÿ”— FLUX.2-small-decoder: black-forest-labs/FLUX.2-small-decoder
๐Ÿ”— GitHub: https://github.com/PRITHIVSAKTHIUR/Flux.2-4B-Encoder-Comparator
๐Ÿš Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

๐Ÿค— > App built on the Gradio SDK. To learn more, visit the app page or the respective model pages.
prithivMLmodsย 
posted an update 3 months 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. ๐Ÿ‘‡

๐Ÿ”—Gemma 4 Compression(s)- https://huggingface.co/collections/prithivMLmods/gemma-4-compressions
๐Ÿ”—Gemma 4 Uncensored [MAX] + Compression(s) - [`ฮฒ ]- https://huggingface.co/collections/prithivMLmods/gemma-4-uncensored-max-compressions
๐Ÿ”—Gemma 4 Compression(s) - MoE- https://huggingface.co/collections/prithivMLmods/gemma-4-compressions-moe
๐Ÿ”—Gemma-4 F32 GGUF- https://huggingface.co/collections/prithivMLmods/gemma-4-f32-gguf

๐Ÿค— > To learn more, visit the app page or the respective model pages.
prithivMLmodsย 
posted an update 3 months 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.

๐Ÿค— Demo Space: prithivMLmods/SAM3-Gemma4-CUDA
๐Ÿฅฝ SAM3: facebook/sam3
๐Ÿ”— 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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prithivMLmodsย 
posted an update 3 months 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.

๐Ÿค— Demo Space: prithivMLmods/SAM3-Plus-Qwen3.5
๐Ÿฅฝ SAM3: facebook/sam3
๐Ÿ”— Qwen-3.5: Qwen/Qwen3.5-2B

To learn more, visit the app page or the respective model pages.
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MaziyarPanahiย 
posted an update 4 months ago
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Training mRNA Language Models Across 25 Species for $165

We built an end-to-end protein AI pipeline covering structure prediction, sequence design, and codon optimization. After comparing multiple transformer architectures for codon-level language modeling, CodonRoBERTa-large-v2 emerged as the clear winner with a perplexity of 4.10 and a Spearman CAI correlation of 0.40, significantly outperforming ModernBERT. We then scaled to 25 species, trained 4 production models in 55 GPU-hours, and built a species-conditioned system that no other open-source project offers. Complete results, architectural decisions, and runnable code below.

https://huggingface.co/blog/OpenMed/training-mrna-models-25-species
prithivMLmodsย 
posted an update 4 months 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.

๐Ÿ”ฅ Demo Space: https://huggingface.co/spaces/prithivMLmods/flux-klein-kv-edit-consistency
๐Ÿค— Model: black-forest-labs/FLUX.2-klein-9b-kv
๐Ÿค— Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
๐Ÿ”— Gradio Server Mode: https://www.gradio.app/main/guides/server-mode

โž” 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.

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

To learn more, visit the app page or the respective model pages.
MaziyarPanahiย 
posted an update 4 months ago
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We annotated 119K medical images with two frontier VLMs (Qwen 3.5, Kimi K2.5), cross-validated at 93% agreement, and produced 110K training records, all for under $500. Fine-tuning 3 small models (2-3B params) improved all benchmarks: best model reaches +15.0% average exact match.

Everything is open-sourced: datasets, adapters, and code.

https://huggingface.co/blog/OpenMed/synthvision
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