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hesamation

posted an update 3 days ago

Post

3743

a senior engineer at google just dropped a 400-page free book on docs for review: agentic design patterns.

the table of contents looks like everything you need to know about agents + code:
> advanced prompt techniques
> multi-agent patterns
> tool use and MCP
> you name it

read it here: https://docs.google.com/document/d/1rsaK53T3Lg5KoGwvf8ukOUvbELRtH-V0LnOIFDxBryE/edit?tab=t.0#heading=h.pxcur8v2qagu

you can also pre-order on Amazon (published by Springer) and the royalties goes to Save the Children: https://www.amazon.com/Agentic-Design-Patterns-Hands-Intelligent/dp/3032014018/

prithivMLmods

posted an update 1 day ago

Post

2521

Dropped the HeadshotX : a super-realistic headshot adapter for Qwen/Qwen-Image, an image generation model by Qwen. It is an advanced LoRA adaptation of the Qwen-Image model and an upgraded version of prithivMLmods/Qwen-Image-Studio-Realism, offering more precise portrait rendering with a strong focus on realism. The model was trained on diverse face types from across the world, labeled with florence2-en and caption-optimized using prithivMLmods/DeepCaption-VLA-7B. 11(types) × 5 different face types: Asian, Hispanic, Caucasian, Latina, Middle Eastern, etc.

⮞ Model🤗: prithivMLmods/Qwen-Image-HeadshotX

⮞ The Previous Adapter (LoRA): prithivMLmods/Qwen-Image-Studio-Realism

⮞ Collection: prithivMLmods/qwen-image-exp-lora-68a978fe11400bc3165b0c4d

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

2 replies

MonsterMMORPG

posted an update 1 day ago

Post

2186

SUPIR is Still Unchallanged Image Upscaler — Supports GPUs starting from RTX 1000 series to RTX 5000 series

App Download Link
You can download SUPIR app from here : https://www.patreon.com/posts/99176057

CHECK BELOW SCREENSHOTS

It has 1-click installers for Windows (only Python 3.10.11 and Git should be sufficient), RunPod (official Pytorch 2.2.0 template) and Massed Compute template Creator > SECourses

App Info
SUPIR: Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild 1 click installer scripts.

SUPIR Sampler and Text CFG Comparison : https://imgsli.com/MjU2ODQz/2/1

Gemini 2.5 Pro prompt to get image description for free :

describe this image for sdxl. write single line prompt to regenerate it exactly same. make the prompt extremely detailed

https://aistudio.google.com/prompts/new_chat

Use Default preset for highest loyalty and Replicate preset for adding more details

Human upscale from 1024x1024 to 3072x3072 (3x upscale and total 9x resolution) with face restore comparison

https://imgsli.com/NDEzMDYx

Owl upscale from 1024x1024 to 3072x3072 (3x upscale and total 9x resolution)

https://imgsli.com/NDEzMDYy

Video Tutorials
Tutorials are older but hopefully a newer one will be made and they should be still useful

Complete Guide to SUPIR Enhancing and Upscaling Images Like in Sci-Fi Movies on Your PC

How To Install SUPIR On RunPod and Massed Compute

How To Install & Use SUPIR : SOTA Image Upscaler On RunPod — 1 Click Easy Install & Run

6 September 2025 Update V91
Libraries upgraded to Torch 2.8, CUDA 12.9, xFormers 0.0.33, Flash Attention 2.8.3

You don’t need to have CUDA or anything else installed and it should work with Python 3.10.11 and Git installed

When compiling libraries, I added support for all GPUs starting from RTX 1000 to 5000 series including other GPUs like A100, H100, B200, L40, etc

Compiled for TORCH_CUDA_ARCH_LIST=6.1;7.5;8.0;8.6;8.9;9.0;10.0;12.0

Kseniase

posted an update about 16 hours ago

Post

1262

10 Latest Preference Optimization Techniques

Models need feedback on what makes outputs “good” or “bad.” Policy optimization (PO) turns preferences and rewards into actual training signals. This field is evolving quickly, moving far beyond classics like PPO and GRPO. So here is our overview of 10 newest PO methods:

1. Pref-GRPO → Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning (2508.20751)
Stabilizes text-to-image reinforcement learning (RL) with pairwise preference rewards and a unified UNIGENBENCH benchmark

2. PVPO (Policy with Value Preference Optimization) → PVPO: Pre-Estimated Value-Based Policy Optimization for Agentic Reasoning (2508.21104)
This critic-free RL method uses a pre-trained model as a reference anchor to reduce bias and guide learning, selecting high-value examples through data pre-sampling

3. DCPO (Dynamic Clipping Policy Optimization) → DCPO: Dynamic Clipping Policy Optimization (2509.02333)
Uses dynamic clipping, which adjusts probability limits per token for better token exploration, and smooth reward standardization to balance rewards over training steps and prevent wasted updates

4. ARPO (Agentic Reinforced Policy Optimization) → Agentic Reinforced Policy Optimization (2507.19849)
Optimizes multi-turn LLM agents that use external tools. It uses an entropy-based adaptive rollout to explore post-tool use and an advantage attribution method to better assign credit across steps, leading to more efficient tool use with fewer resources

5. GRPO-RoC (Group Relative Policy Optimization with Resampling-on-Correct) → rStar2-Agent: Agentic Reasoning Technical Report (2508.20722)
Oversamples rollouts, then resamples them to keep diverse mistakes and only the highest-quality correct answers. It reduces noises and ends up with stronger reasoning in a code environment

Read further below ⬇️
If you like this, also subscribe to the Turing post: https://www.turingpost.com/subscribe

1 reply

prithivMLmods

posted an update 2 days ago

Post

3091

Comparing: DeepCaption-VLA-7B, built on Qwen2.5-VL-7B-Instruct, is tailored for image captioning and vision-language attribution, focusing on precise, descriptive captions of visual properties, object attributes, and scene details. In contrast, Qwen2.5-VL-7B-Abliterated-Caption-it is fine-tuned for abliterated captioning, generating highly detailed descriptions across diverse visual categories.

Models🤗
✦ DeepCaption-VLA-7B : prithivMLmods/DeepCaption-VLA-7B
✦ Qwen2.5-VL-7B-Abliterated-Caption-it : prithivMLmods/Qwen2.5-VL-7B-Abliterated-Caption-it

Spaces⛵
➜ VisionScope-R2 : prithivMLmods/VisionScope-R2
➜ Qwen2.5-VL-Outpost : prithivMLmods/Qwen2.5-VL-Outpost

Collection🗞️
DeepCaption attr. : prithivMLmods/deepcaption-attr-68b041172ebcb867e45c556a
VL Abliterated-Caption : prithivMLmods/vl-abliterated-caption-68a0443b63182e97a15c47a3
Multimodal VLMs - Until July'25 : prithivMLmods/multimodal-vlms-until-july25-688312e6b840e1e156f13027
Multimodal VLMs - Aug'25 : prithivMLmods/multimodal-vlms-until-july25-688312e6b840e1e156f13027

GitHub↗️
> DeepCaption-VLA-7B [4bit-notebook demo] : https://github.com/PRITHIVSAKTHIUR/Multimodal-Outpost-Notebooks/blob/main/DeepCaption-VLA-7B%5B4bit%20-%20notebook%20demo%5D/DeepCaption-VLA-7B.ipynb
> Qwen2.5-VL-3B-Abliterated-Caption-it(caption) : https://github.com/PRITHIVSAKTHIUR/Multimodal-Outpost-Notebooks/blob/main/Qwen2.5-VL-3B-Abliterated-Caption-it(caption)/Qwen2_5_VL_3B_Abliterated_Caption_it.ipynb

The community GPU grant was given by Hugging Face — special thanks to them. 🤗🚀

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

DualityAI-RebekahBogdanoff

posted an update 2 days ago

Post

3373

Shout out to the winners of the "Synthetic2Real Object Detection Challenge" Duality AI hosted earlier this year. Out of the 1000+ participants in our challenges, these users stood out above the rest.

🥇 1st place: Kaggle user "richardtroy"

🥈 2nd place: @sergio-sanz-rodriguez

🥉 3rd place: @Nadiaaaaaaa

View the entire leaderboard at - https://tinyurl.com/38ebvcwf

Join our current Grocery Items: Multi-Class Object Detection Synthetic2Real Kaggle competition here: https://tinyurl.com/y224rttu

And be on the lookout for anther competition in the next couple weeks with a brand new domain!
hint: ✈️

burtenshaw

posted an update 3 days ago

Post

2388

The open source AI community is just made of people who are passionate and care about their work. So we thought it would be cool to share our favourite icons of the community with a fun award.

Winners get free Hugging Face Pro Subscriptions, Merchandise, or compute credits for the hub.

🔗 Follow and nominate here:

community-spotlight

This is a new initiative to recognise and celebrate the incredible work being done by community members. It's all about inspiring more collaboration and innovation in the world of machine learning and AI.

They're highlighting contributors in four key areas:
- model creators: building and sharing innovative and state-of-the-art models.
- educators: sharing knowledge through posts, articles, demos, and events.
- tool builders: creating the libraries, frameworks, and applications that we all use.
- community champions: supporting and mentoring others in forums.

Know someone who deserves recognition? Nominate them by opening a post in the Hugging Face community forum.

1 reply

MonsterMMORPG

posted an update 3 days ago

Post

3644

Qwen Image LoRA trainings Stage 1 results and pre-made configs published - As low as training with 6 GB GPUs - Stage 2 research will hopefully improve quality even more - Images generated with 8-steps lightning LoRA + SECourses Musubi Tuner trained LoRA in 8 steps + 2x Latent Upscale

1-click to install SECourses Musubi Tuner app and pre-made training configs shared here : https://www.patreon.com/posts/137551634

Hopefully a full video tutorial will be made after Stage 2 R&D trainings completed

Example training made on the hardest training which is training a person and it works really good. Therefore, it shall work even much better on style training, item training, product training, character training and such

Stage 1 took more than 35 unique R&D Qwen LoRA training

1-Click installer currently fully supporting Windows, RunPod (Linux & Cloud) and Massed Compute (Linux & recommend Cloud) training for literally every GPU like RTX 3000, 4000, 5000 series or H100, B200, L40, etc

28 images weak dataset is used for this training

More angles having dataset would perform definitely better

Moreover, i will make a research for a better activation token as well rather than ohwx

After Stage 2, I am expecting hopefully much better results

As a caption, i recommend to use only ohwx nothing else, not even class token

Higher quality more images shared here : https://medium.com/@furkangozukara/qwen-image-lora-trainings-stage-1-results-and-pre-made-configs-published-as-low-as-training-with-ba0d41d76a05

Image prompts randomly generated with Gemini 2.5 in Google AI Studio for free

How to Generate Images
In the zip file of this post : https://www.patreon.com/posts/114517862

We have Amazing_SwarmUI_Presets_v21.json made for SwarmUI

Import it and i am using Qwen Image 8 Steps Ultra Fast to generate images and then apply Upscale Images 2X to make them 4x resolution (1328x1328 to 2656x2656)

Of course in addition to preset don't forget to select your trained LoRA

andywu-kby

posted an update about 1 hour ago

Post

Hello everyone
Good day!

We have launched the product - Virtual Try On 🚀
Say goodbye to the uncertainty of online shopping with Miragic’s Virtual Try-On solution! Our cutting-edge AI technology lets you try on clothes virtually, offering a seamless and interactive shopping experience. Whether you're exploring new outfits or simply trying before you buy, Miragic gives you a realistic view of how items will look on you—without ever stepping into a store.

Miragic-AI/Miragic-Virtual-Try-On

🌟 Key Features:
- Realistic 3D Try-On: See how clothes fit and look on your virtual self in real-time.
- Personalized Fit: Using advanced body-scanning tech, Miragic adjusts the fit based on your unique measurements.
- Wide Fashion Selection: Browse through various brands and styles, all available for a virtual try-on.
- Sustainable Shopping: Reduce the need for returns and make more eco-friendly choices with a virtual experience that helps you shop smarter.

👚 Why Virtual Try-On?
- Save time and money while shopping smarter.
- Discover new styles, fit options, and combinations in a way that’s fast and fun.
- Enjoy a unique, tech-driven shopping experience from the comfort of your home!

Join us today and transform the way you shop online with Virtual Try-On.

dhruv3006

posted an update 2 days ago

Post

282

Cua: Best State-of-the-Art Computer-Use Agent

Build a SOTA Computer-Use Agent using Cua (https://github.com/trycua/cua), the open-source infrastructure and agent framework for controlling real desktop and browser environments.
Submissions are evaluated in HUD’s OSWorld-Verified benchmarking environment. The top-scoring team earns a secured interview with a Y Combinator partner for the next batch.

Prizes:
Guaranteed YC partner interview
Feature on the Cua blog + social channels
Swag pack for each team member

Eligibility: To be considered for judging and prizes, sign up at https://www.trycua.com/hackathon

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