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prithivMLmods 
posted an update about 23 hours ago
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VIGOR (Vision Intelligence and Guardrail Oriented Reasoning) is now available on the Hugging Face Model Hub. It is a multimodal vision classification model based on Qwen3.5, designed for visual content-safety analysis and conservative classification, with a particular focus on identifying potentially sensitive content.

📦 Models: 27B, 9B, 4B —

prithivMLmods/VIGOR-27B,
prithivMLmods/VIGOR-flash,
prithivMLmods/VIGOR-mini

↗️ Collection:
https://huggingface.co/collections/prithivMLmods/vigor

To learn more, visit the app page or the respective model pages.
javadtaghia 
posted an update 3 days ago
prithivMLmods 
posted an update 10 days ago
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998
Flux-3-Image-Klein-LoRAs-Fast is now live on Hugging Face Spaces.🤗🔥

Plug and play with any custom LoRAs based on flux-3-image-klein. 16-step distilled fast inference, with support for prompt upsampling. More LoRAs will be added in the coming days!

🔗 Space: prithivMLmods/flux-3-image-klein-loras-fast

🔗 Image Generation Apps Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

🔗 GitHub: https://github.com/PRITHIVSAKTHIUR/flux-3-image-klein-loras-fast

To learn more, visit the app page or the respective model pages.
javadtaghia 
posted an update 10 days ago
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1,103
Hugging face article: https://huggingface.co/blog/javadtaghia/atmem-2310-bounded-evidence-discovery-for-persiste

AtMem 2.3.10 is out; and our full DolphinBench result has more than doubled.

AtMem 2.3.9 passed 192 of 600 tasks (32%).

AtMem 2.3.10 passed 390 of 600 (65%). We doubled it.

What changed?
We focused on how an agent discovers and uses evidence.
AtMem combined lexical and semantic retrieval while keeping related passages together with their original source and provenance and more.

Where do we stand?
This is substantial progress, with a clear tradeoff: median recorded task latency increased from 31.87 to 85.78 seconds. More successful investigation currently takes more time.
The published Hermes/Luna/Mem0 reference scores 424/600 (70.7%).

What comes next?
We want to understand the remaining failures: was evidence missing, poorly ranked, packed incompletely, interpreted with the wrong temporal state, or used incorrectly during an action?
Evidence discovery remains opt-in.
Release: https://github.com/aetna000/atmem/releases/tag/v2.3.10
DolphinBench submission PR: https://github.com/mem0ai/dolphinbench/pull/10
Results and execution evidence: atmem/atmem-2.3.10b1-dolphinbench

PS: DolphinBench tests whether an agent can use a simulated user’s history to complete actions in applications. Finding a relevant passage isn’t enough—a task passes only when all its required checks pass.
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javadtaghia 
posted an update 14 days ago
javadtaghia 
posted an update 18 days ago
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It is not always positive results that worth noting.
I ran a long run of training to improve AtMem (agent memory) on storage path using Laya as a decision model. However, I found it did not give me any better result than original AtMem.
Indeed we can use laya on the retrieval path, we have used than by pluging Jev. So we kinda proved something that is still a gap in memory systems (improving storage) is not as easy as it sounds. Check details https://huggingface.co/blog/javadtaghia/we-fine-tuned-a-memory-classifier-for-our-agent-he
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javadtaghia 
posted an update 24 days ago
javadtaghia 
posted an update 26 days ago
prithivMLmods 
posted an update 27 days ago
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4,767
OneDecision-VisionGuard-Demo is now available on Hugging Face Spaces!

🤗 Space: prithivMLmods/OneDecision-VisionGuard-Demo

This demo showcases the OneDecision-VisionGuard family of multimodal image classification models for detecting NSFW and other sensitive visual content, with structured JSON reasoning, improved accuracy, and better handling of edge cases such as sensitive imagery, uncensored analysis, scene descriptions, and classification reasoning.

📦 Models: 27B, 9B, 4B — prithivMLmods/OneDecision-VisionGuard-27B-SFT, prithivMLmods/OneDecision-VisionGuard-9B-SFT, prithivMLmods/OneDecision-VisionGuard-4B-SFT

↗️ Collection: https://huggingface.co/collections/prithivMLmods/onedecision-visionguard

To learn more, visit the app page or the respective model pages.
javadtaghia 
posted an update about 1 month ago
javadtaghia 
posted an update about 1 month ago
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I’m preparing to submit my article to arXiv and need an endorsement for the cs.AI category.

If you’re eligible to endorse submissions in this area and would be willing to help, I’d really appreciate it. Please DM me and I can send you the arXiv endorsement link.

Thank you!

from arXiv cs.AI community, can anyone support me?
arudradey 
posted an update about 1 month ago
prithivMLmods 
posted an update about 1 month ago
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3,966
Qwen-Image-2.1 Plug and Play LoRA App is now live on Hugging Face Spaces.

🔗 Space: prithivMLmods/Qwen-Image-2.1-LoRAs-PnP

It supports standard inference, 4-step Turbo inference, custom LoRA lazy repacks, and LoRA Plug and Play (PnP), all in one setting!

🔗 Qwen-Image-2.1 Image-to-Image LoRAs: https://huggingface.co/collections/prithivMLmods/qwen-image-21-image-to-image-loras

🔗 GitHub: https://github.com/PRITHIVSAKTHIUR/Qwen-Image-2.1-LoRAs-PnP

To learn more, visit the app page or the respective model pages.
prithivMLmods 
posted an update about 2 months ago
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VisionGuardrail EVO-2, a multimodal image-classification content-safety model based on Qwen/Qwen3.8-27B, is now available on the Hub!

Stricter image classification than before, with a dense 27-billion-parameter multimodal model, more precise reasoning, and improved captions for classifying visual media.

➠ Models: prithivMLmods/VisionGuardrail-Evo2-27B, prithivMLmods/VisionGuardrail-Evo2-27B-GGUF

➠ Collection: https://huggingface.co/collections/prithivMLmods/visionguardrail-evo2

➠ Previous Models: https://huggingface.co/collections/prithivMLmods/visionguardrail-collection

⤷ To learn more, visit the app page or the respective model pages.
prithivMLmods 
posted an update about 2 months ago
prithivMLmods 
posted an update about 2 months ago
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VisionGuardrail, a multimodal content-safety classifier based on Qwen3.5, is now available on Hugging Face in 4B and 9B variants. It is a direct upgrade to ImageShield-MMCF, providing improved parental controls through conservative visual content-safety filtering.

More About:
➠ hf.co/blog — https://huggingface.co/blog/prithivMLmods/vision-guardrail-mini-blog

➠ Models:
✦ VisionGuardrail-4B: prithivMLmods/VisionGuardrail-4B
✦ VisionGuardrail-9B: prithivMLmods/VisionGuardrail-9B

➠ Dataset:
✦ ImageShield-Guardrail-Pro: prithivMLmods/ImageShield-Guardrail-Pro

⤷ To learn more, visit the app page or the respective model pages.
prithivMLmods 
posted an update 2 months ago
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3,117
ImageShield-MMCF — Multimodal Content Filter is a multimodal content-safety classifier built on top of Qwen3.5 and is now available on Hugging Face!

This is the preview initial version (v1.0) of the model, designed to classify visual content as Safe or Unsafe, with a particular focus on detecting Not Safe for Work (NSFW) and other potentially sensitive visual content.

The demo is implemented in the prithivMLmods/opencaption-4b-vl-sft Space, which serves as an active content-safety layer for computer vision tasks. It helps block Not Safe for Work (NSFW) content generation and paves the way for more meaningful and responsible creativity.

⊹ ImageShield-MMCF-0.8B: prithivMLmods/ImageShield-MMCF-0.8B
⊹ ImageShield-MMCF-2B: prithivMLmods/ImageShield-MMCF-2B
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seawolf2357 
submitted a paper to Daily Papers 2 months ago
prithivMLmods 
posted an update 3 months ago
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5,298
The Qwen3.8 27B demo for object grounding is now available on Hugging Face Spaces.

It features three tasks: Object Detection (Bounding Boxes), Point Localization (Keypoints), and Spatial Guidance (Path Mapping).

Try it now: prithivMLmods/Qwen3.8-27B-Object-Detection
prithivMLmods 
posted an update 3 months ago
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5,582
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.🤗

➠ Image-to-3D-Video-Asset-Generator: prithivMLmods/Image-to-3D-Video-Asset-Generator
➠ collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
➠ github: https://github.com/PRITHIVSAKTHIUR/Image-to-3D-Video-Asset-Generator

⤷ To learn more, visit the app page or the respective model pages.