OpenGVLab (OpenGVLab)

posted an update about 4 hours ago

Post

213

LTX-2 Camera-Control LoRA demo with dolly-in/out and dolly-left/right is now available on Hugging Face, paired with ltx-2-19b-distilled-lora for fast inference. It also includes dynamic GPU duration adjustments for long video generations. Click the related Space links below.

🤗Try it now on : prithivMLmods/LTX-2-LoRAs-Camera-Control-Dolly
⭐Github: https://github.com/PRITHIVSAKTHIUR/LTX-2-LoRAs-Camera-Control-Dolly
🕹️Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

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

Nymbo

posted an update 4 days ago

Post

1561

Genuine recommendation: You should really use this AutoHotKey macro. Save the file as macros.ahk and run it. Before sending a prompt to your coding agent, press Ctrl + Alt + 1 and paste your prompt to any regular chatbot. Then send the output to the agent. This is the actual, boring, real way to "10x your prompting". Use the other number keys to avoid repeating yourself over and over again. I use this macro prolly 100-200 times per day. AutoHotKey isn't as new or hype as a lot of other workflows, but there's a reason it's still widely used after 17 years. Don't overcomplicate it.

; Requires AutoHotkey v1.1+

; All macros are `Ctrl + Alt + <variable>`

^!1::
    Send, Please help me more clearly articulate what I mean with this message (write the message in a code block):
return

^!2::
    Send, Please make the following changes:
return

^!3::
    Send, It seems you got cut off by the maximum response limit. Please continue by picking up where you left off.
return

In my experience the past few months, Ctrl + Alt + 1 works best with Instruct models (non-thinking). Reasoning causes some models to ramble and miss the point. I've just been using GPT-5.x for this.

prithivMLmods

posted an update 7 days ago

Post

2356

Dropping Image Edit (Object Manipulator): Add or remove specified objects/designs, with flexible support for both single-image and multi-image modes.

🤗 Demo: prithivMLmods/Qwen-Image-Edit-Object-Manipulator

Qwen-Image-Edit-2511-Object-Remover is an adapter (LoRA) developed for Qwen’s Qwen-Image-Edit-2511 image-to-image model. It is specifically designed for precise object removal from images.

⭐ Model: prithivMLmods/Qwen-Image-Edit-2511-Object-Remover

Qwen-Image-Edit-2511-Object-Adder is an adapter (LoRA) developed for Qwen’s Qwen-Image-Edit-2511 image-to-image model. It is specifically designed for precise object addition to images.

⭐ Model: prithivMLmods/Qwen-Image-Edit-2511-Object-Adder

🕹️ Collection: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-object-manipulator
🕹️ github: https://github.com/PRITHIVSAKTHIUR/Qwen-Image-Edit-Object-Manipulator

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

prithivMLmods

posted an update 14 days ago

Post

4097

Update: TRELLIS.2 (Text to 3D, Image to 3D) Gradio with Rerun Embedded demo with improved visualization of the 3D model previewer is now available on Hugging Face. Generate assets and view them in the 3D viewer, powered and streamlined with Microsoft’s TRELLIS.2 and Tongyi-MAI’s Z-Image-Turbo models.

🤗 TRELLIS.2 (Demo): prithivMLmods/TRELLIS.2-Text-to-3D
🕹️ GitHub: https://github.com/PRITHIVSAKTHIUR/TRELLIS.2-Text-to-3D-RERUN
🕹️ Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations

To know more about it, visit the app page or the respective model page!

prithivMLmods

posted an update 15 days ago

Post

4184

Introducing the Qwen-Image-Edit-2511-LoRAs-Fast demo, featuring image property comparison and contrast, built on top of Gradio and the combined Rerun SDK. It supports single and multi-image edits with existing LoRAs that are lazily loaded. (Note: This is still an experimental Space for Qwen-Image-Edit-2511.)

⭐ Space Demo: prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast
⭐ GitHub: https://github.com/PRITHIVSAKTHIUR/Qwen-Image-Edit-2511-LoRAs-Fast-Multi-Image-Rerun
⭐ Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

To know more about it, visit the app page or the respective model page!

2 replies

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lll2343

updated 3 models 15 days ago

revliter

updated a collection 19 days ago

InternVideo-Next

Collection

InternVideo-Next: Towards General Video Foundation Models without Video-Text Supervision • 5 items • Updated 19 days ago • 4

prithivMLmods

posted an update 22 days ago

Post

3697

Introducing demos for new SOTA models from AI2: SAGE-MM (Smart Any-Horizon Agents for Long-Video Reasoning) and Molmo-2, an open vision-language model that supports multi-image (QA and pointing) and video (QA, pointing, and tracking). The respective demo-related collections are listed below. 🎃🔥

✨ SAGE-MM [Video-Reasoning]: prithivMLmods/SAGE-MM-Video-Reasoning
✨ Molmo2 [Demo]: prithivMLmods/Molmo2-HF-Demo

🎃 GitHub[SAGE-MM]: https://github.com/PRITHIVSAKTHIUR/SAGE-MM-Video-Reasoning
🎃 GitHub[Molmo2]: https://github.com/PRITHIVSAKTHIUR/Molmo2-HF-Demo
🎃 Multimodal Implementations: https://huggingface.co/collections/prithivMLmods/multimodal-implementations

To know more about it, visit the app page or the respective model page!

1 reply

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vansin

posted an update 22 days ago

Post

259

QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management

prithivMLmods

posted an update 23 days ago

Post

2059

Introducing TRELLIS.2 Text-to-3D. The demo for the TRELLIS.2-4B (Image-to-3D) model is streamlined with the Z-Image Turbo image generation model to enable Text-to-3D functionality. There is no need for input assets, making a small leap forward for ideation. Optionally, it also includes default support for Image-to-3D inference using direct image assets. Find the demo and related collections below... 🤗🔥

✨ TRELLIS.2-Text-to-3D [Demo]: prithivMLmods/TRELLIS.2-Text-to-3D
✨ Multimodal Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
✨ Github: https://github.com/PRITHIVSAKTHIUR/TRELLIS.2-Text-to-3D

To know more about it, visit the app page or the respective model page!

Eurayka

authored a paper 23 days ago

VKnowU: Evaluating Visual Knowledge Understanding in Multimodal LLMs

Paper • 2511.20272 • Published Nov 25, 2025 • 1

Nymbo

posted an update 24 days ago

Post

2023

🚨 New tool for the Nymbo/Tools MCP server: The new Agent_Skills tool provides full support for Agent Skills (Claude Skills but open-source).

How it works: The tool exposes the standard discover/info/resources/validate actions. Skills live in /Skills under the same File_System root, and any bundled scripts run through Shell_Command, no new infrastructure required.

Agent_Skills(action="discover")  # List all available skills
Agent_Skills(action="info", skill_name="music-downloader")  # Full SKILL.md
Agent_Skills(action="resources", skill_name="music-downloader")  # Scripts, refs, assets

I've included a music-downloader skill as a working demo, it wraps yt-dlp for YouTube/SoundCloud audio extraction.

Caveat: On HF Spaces, Shell_Command works for most tasks, but some operations (like YouTube downloads) are restricted due to the container environment. For full functionality, run the server locally on your machine.

Try it out ~ https://www.nymbo.net/nymbot

prithivMLmods

posted an update 25 days ago

Post

2021

Demo for Molmo2 on Hugging Face is live now, including Single/Multi-Image VQA, Visual Pointing/Grounding, Video VQA, and Video Point Tracking. Find the demo and related collections below. 🔥🤗

● Molmo2 HF Demo🖥️: prithivMLmods/Molmo2-HF-Demo
● Model Collection: https://huggingface.co/collections/allenai/molmo2
● Related Multimodal Space Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations

To know more about it, visit the app page or the respective model page!

prithivMLmods

posted an update 26 days ago

Post

5547

Introducing the Z Image Turbo LoRA DLC App, a gallery space for plug-and-play Z-Image-Turbo LoRAs. It features a curated collection of impressive LoRAs for generating high-quality images. By default, it runs on the base model. Simply choose a LoRA, type your prompt, and generate images. You can find the app and more details below. 🤗🧪

● Space [Demo]: prithivMLmods/Z-Image-Turbo-LoRA-DLC
● Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
● Check the list of Z-Image LoRA's: https://huggingface.co/models?other=base_model:adapter:Tongyi-MAI/Z-Image-Turbo
● Github: https://github.com/PRITHIVSAKTHIUR/Z-Image-Turbo-LoRA-DLC

Other related image gen spaces:-

● FLUX-LoRA-DLC2: prithivMLmods/FLUX-LoRA-DLC2
● FLUX-LoRA-DLC: prithivMLmods/FLUX-LoRA-DLC
● Qwen-Image-LoRA-DLC: prithivMLmods/Qwen-Image-LoRA-DLC
● Qwen-Image-Edit-2509-LoRAs-Fast: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast
● Qwen-Image-Edit-2509-LoRAs-Fast-Fusion: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast-Fusion

& more...

To know more about it, visit the app page or the respective model page!

2 replies

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KingNish

posted an update about 1 month ago

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2478

Muon vs MuonClip vs Muon+Adamw

Muon has gone from an experiment to a mainstream optimizer, but does it hold up for fine‑tuning? We ran head‑to‑head tests on Qwen3‑4B (10k+ high‑quality instruction rows) to find out.

Short story: Pure Muon converged fastest at the start, but its gradient‑norm spikes made training unstable. MuonClip (Kimi K2’s clipping) stabilizes long pretraining runs, yet in our small‑scale fine‑tune it underperformed, lower token accuracy and slower convergence. The winner was the hybrid: Muon for 2D layers + AdamW for 1D layers. It delivered the best balance of stability and final performance and even beat vanilla AdamW.

Takeaway: for small-scale fine-tuning, hybrid = practical and reliable.

Next Step: scale to larger models/datasets to see if Muon’s spikes become catastrophic or if clipping wins out.

Full Blog Link: https://huggingface.co/blog/KingNish/optimizer-part1

KingNish

posted an update about 1 month ago

Post

2508

I tested Muon vs MuonClip vs Muon+AdamW for fine-tuning LLMs
Just published a blog on that, Read here 👉 https://huggingface.co/blog/KingNish/optimizer-part1

1 reply

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prithivMLmods

posted an update about 1 month ago

Post

2741

Introducing the D.Markdown Experimental Models, Proxima and Epsilon OCR models, built on top of Qwen3-VL and Qwen2.5-VL respectively. Proxima is optimized for Markdown generation and is capable of embedding inline programming code snippets and generating rich nodes such as HTML, XML, JSON, and YAML. Epsilon is optimized for reconstructing complex layouts including tables, forms, and mathematical content. 🌌✨

● proxima-ocr-d.markdown-post3.0.l: prithivMLmods/proxima-ocr-d.markdown-post3.0.l
● epsilon-ocr-d.markdown-post3.0.m: prithivMLmods/epsilon-ocr-d.markdown-post3.0.m
● proxima-ocr-d.markdown-post3.0.l-gguf: prithivMLmods/proxima-ocr-d.markdown-post3.0.l-GGUF
● epsilon-ocr-d.markdown-post3.0.m-gguf: prithivMLmods/epsilon-ocr-d.markdown-post3.0.m-GGUF

● Collection: https://huggingface.co/collections/prithivMLmods/dynamic-markdowns
● Multimodal Apps: https://huggingface.co/collections/prithivMLmods/multimodal-implementations

👉 These models are stage progression models, and currently they may contain artifacts.

To know more about it, visit the app page or the respective model page!

prithivMLmods

posted an update about 1 month ago

Post

1137

Try CUA GUI Operator 🖥️ Space, the demo of some interesting multimodal ultra-compact Computer Use Agent (CUA) models in a single app, including Fara-7B, UI-TARS-1.5-7B, and Holo models, to perform GUI localization tasks.

● CUA-GUI-Operator [Demo]: prithivMLmods/CUA-GUI-Operator
● Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations

Other related multimodal spaces

● Qwen3-VL: prithivMLmods/Qwen3-VL-HF-Demo
● Multimodal-VLM-v1.0: prithivMLmods/Multimodal-VLM-v1.0
● Vision-to-VibeVoice-en: prithivMLmods/Vision-to-VibeVoice-en

I have planned to add Chrome sandboxes to streamline it and turn it into a browser based CUA multimodal tool, which will be added to the same space soon.

To know more about it, visit the app page or the respective model page!