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sayakpaul  authored a paper 12 days ago
From Reflection to Perfection: Scaling Inference-Time Optimization for Text-to-Image Diffusion Models via Reflection Tuning
1024m  authored a paper 18 days ago
Robust and Fine-Grained Detection of AI Generated Texts
1024m  authored a paper 20 days ago
Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance
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data-is-better-together-contributor's activity

ZennyKenny 
posted an update 1 day ago
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1724
When I heard the Reasoning Dataset Competition deadline was extended to 9 May, I knew I had time to get in one more entry. 🔥🔥🔥

With the rise of Vibe Coding, and the potential risks that are introduced by humans letting LLMs build their apps for them, lots of people are (rightfully) concerned about the safety of the code that is hitting prod.

In response to that, I'm happy to present my final submission to the Reasoning Dataset Competition and attempt to start benchmarking the ability of LLMs to identify unsafe and / or exploitable code by way of the CoSa (Code Safety) benchmark: ZennyKenny/cosa-benchmark-dataset

Currently a curated set of 200 examples, calibrated on OpenAI's standard issue models (GPT-4.1, o4 mini, and GPT-3.5 Turbo) as "baseline performance" (70% decile). Check it out and drop a ❤️ if you think it could be useful or hit the Community section with suggestions / critiques.
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prithivMLmods 
posted an update 2 days ago
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734
The new versions of Midjourney Mix adapters have been dropped in stranger zone hf. These adapters excel in studio lighting portraits and painterly styles, trained using the style of strangerzonehf/Flux-Midjourney-Mix2-LoRA. They leverage 24-bit colored synthetic images generated form midjourney v6 to achieve high-quality image reproducibility and support adaptable aspect ratios, using Flux.1 as the base model. 🥳

Models [ ⌗ ]

> Flux-Midjourney-Painterly-LoRA : strangerzonehf/Flux-Midjourney-Painterly-LoRA
> Flux-Midjourney-Studio-LoRA : strangerzonehf/Flux-Midjourney-Studio-LoRA

> Collection : strangerzonehf/midjourney-mix-3-ft-flux1-dev-68165d58a2a08025852d63f3

> Space : prithivMLmods/FLUX-LoRA-DLC2

The best dimensions and inference settings for optimal results are as follows: A resolution of 1280 x 832 with a 3:2 aspect ratio is recommended for the best quality, while 1024 x 1024 with a 1:1 aspect ratio serves as the default option. For inference, the recommended number of steps ranges between 30 and 35 to achieve optimal output.
fdaudens 
posted an update 3 days ago
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2593
Forget everything you know about transcription models - NVIDIA's parakeet-tdt-0.6b-v2 changed the game for me!

Just tested it with Steve Jobs' Stanford speech and was speechless (pun intended). The video isn’t sped up.

3 things that floored me:
- Transcription took just 10 seconds for a 15-min file
- Got a CSV with perfect timestamps, punctuation & capitalization
- Stunning accuracy (correctly captured "Reed College" and other specifics)

NVIDIA also released a demo where you can click any transcribed segment to play it instantly.

The improvement is significant: number 1 on the ASR Leaderboard, 6% error rate (best in class) with complete commercial freedom (cc-by-4.0 license).

Time to update those Whisper pipelines! H/t @Steveeeeeeen for the finding!

Model: nvidia/parakeet-tdt-0.6b-v2
Demo: nvidia/parakeet-tdt-0.6b-v2
ASR Leaderboard: hf-audio/open_asr_leaderboard
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burtenshaw 
posted an update 4 days ago
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1359
Qwen 3 Fine tuning >> MoE. Update the experiment thread to include config and script for fine-tuning the Qwen3-30B-A3B model.

The goal is to make a low latency non-thinking model for a daily driver coding, so 3 billion parameters active should be perfect.

✔️ training running
✔️ evals running
⏭️ improve dataset

The moe isn't going to fit into colab's A100 even with quantization (🙏 @UnslothAI ). So I've been working on HF spaces' H100s for this. Everything is available in the tread and I'll share more tomorrow.

burtenshaw/Qwen3-Code-Lite#1
fdaudens 
posted an update 4 days ago
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I just gave my chatbots a massive upgrade: they can now generate audio from text, modify images — you name it. Here’s how:

The Gradio team shipped MCP support. That means you can plug any AI app built with it into Claude or Cursor using the Model Context Protocol (MCP) — think of it like a USB port for LLMs.

I put it to the test:
- Whipped up a quick text-to-speech app with Kokoro on HF (with an LLM riding shotgun, naturally)
- Added "mcp_server=True" in the code
- Connected it to Claude

Now I can generate audio from any text. The possibilities are next-level: you can potentially plug any of the 500K+ AI apps on Hugging Face to your favorite LLM.

Is this the new UI for AI?

- My tts app (feel free to use/duplicate it): fdaudens/kokoro-mcp
- Blog post: https://huggingface.co/blog/gradio-mcp
alielfilali01 
posted an update 4 days ago
fdaudens 
posted an update 5 days ago
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1673
Want to know which AI models are least likely to hallucinate — and how to keep yours from spiking hallucinations by 20%?

A new benchmark called Phare, by Giskard, tested leading models across multiple languages, revealing three key findings:

1️⃣ Popular models aren't necessarily factual. Some models ranking highest in user satisfaction benchmarks like LMArena are actually more prone to hallucination.

2️⃣ The way you ask matters - a lot. When users present claims confidently ("My teacher said..."), models are 15% less likely to correct misinformation vs. neutral framing ("I heard...").

3️⃣ Telling models to "be concise" can increase hallucination by up to 20%.

What's also cool is that the full dataset is public - use them to test your own models or dive deeper into the results! H/t @davidberenstein1957 for the link.

- Study: https://www.giskard.ai/knowledge/good-answers-are-not-necessarily-factual-answers-an-analysis-of-hallucination-in-leading-llms
- Leaderboard: https://phare.giskard.ai/
- Dataset: giskardai/phare
prithivMLmods 
posted an update 5 days ago
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1755
Dropping downstream tasks using newly initialized parameters and weights supports domain-specific image classification post-training, based on the SigLIP-2 models: Patch-16/224, Patch-16/256, and Patch-32/256. For more details, please refer to the respective model cards : 🤗

+ watermark detection : prithivMLmods/Watermark-Detection-SigLIP2
+ resisc45 : prithivMLmods/RESISC45-SigLIP2
+ pacs dg : prithivMLmods/PACS-DG-SigLIP2
+ 3d printed or not : prithivMLmods/3D-Printed-Or-Not-SigLIP2
+ formula or text : prithivMLmods/Formula-Text-Detection

Categorizing Un-Safe Content :
- explicit content patch16 256 : prithivMLmods/siglip2-x256-explicit-content
- explicit content patch32 256 : prithivMLmods/siglip2-x256p32-explicit-content

Collection :
> SigLIP2 Content Filters 042025 Final : https://huggingface.co/collections/prithivMLmods/siglip2-content-filters-04202-final-680fe4aa1a9d589bf2c915ff
> SigLIP2 : google/siglip2-67b5dcef38c175486e240107
> SigLIP2 Multilingual Vision-Language Encoders : https://arxiv.org/pdf/2502.14786
ZennyKenny 
posted an update 5 days ago
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1330
The same way the advent of Adobe Illustrator has led to innovation in the way that creative professionals work, I earnestly believe that AI will do the same (contrary to the popular opinion that it represents some regression in the world of creatives).

@natalika and I were speaking about this topic and like most illustrators she has some understandable concerns about the spread of AI in her field. She also told me how much time she spends generating concept art that will never see the light of day in >98% of cases. 💡

To me, that sounded like a perfect opportunity to leverage image diffusion in a way that helps artists spend more time creating cool stuff rather than just malevolently mining their work and using it without credit. Using the Black Forest Labs base model FLUX, Replicate, and about $5 of H100 compute, I post-trained a LoRA adapter on a set of her images associated with one project she's working on and spun up an app with Hugging Face Spaces (and Zero GPU for the win).

I give you, Natalie Diffusion: ZennyKenny/natalie-diffusion

Now, generating concept art in her particular style takes seconds instead of hours and when it's time to put the work into production, a human designer is still invaluable. And building it in the open hopefully inspires other use cases amongst other designers. 🖖
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ZennyKenny 
posted an update 6 days ago
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2693
I've created a new dataset using the Algorithm of Thoughts architecture proposed by Sel et al. (2023) in a reasoning context. (paper: https://arxiv.org/pdf/2308.10379)

The dataset simulates the discovery phase of a fictitious VC firm called Reasoned Capital and, once expanded, can be used to create models which are able to make complex, subjective financial decisions based on different criteria.

The generation process encourages recursive problem-solving in increasingly complex prompts to encourage models to assess and reevaluate the conclusions and generated opinions of upstream models. Pretty neat stuff, and I'm not aware of this architecture being used in a reasoning context anywhere else.

Check it out: ZennyKenny/synthetic_vc_financial_decisions_reasoning_dataset
prithivMLmods 
posted an update 10 days ago
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2184
Bringing out style-intermixing adapters for Flux.Dev, including Aura Glow, Fallen Ink Art, Cardboard Paper Arts, Black & White Expressions, and Glitter Gem Touch. For more details, visit the model card of the LoRA. 🥳

╰┈➤Demo : prithivMLmods/FLUX-LoRA-DLC2 & prithivMLmods/FLUX-LoRA-DLC

╰┈➤ Adapters :
+ Aura Glow : strangerzonehf/2DAura-Flux
+ Fallen Ink Art : strangerzonehf/FallenArt-Flux
+ Black & White Expressions : strangerzonehf/BnW-Expressions-Flux
+ Glitter Gem Touch : strangerzonehf/Gem-Touch-LoRA-Flux
+ Cardboard Paper Arts v1 : strangerzonehf/Flux-Cardboard-Art-LoRA
+ Cardboard Paper Arts v2 : strangerzonehf/Cardboard-v2-Flux

╰┈➤ Pages :
- Repository Page : strangerzonehf
- Collection : strangerzonehf/mixer-adp-042025-68095c365d9d1072c8d860be
- Flux Ultimate LoRA Collection : strangerzonehf/Flux-Ultimate-LoRA-Collection
- By prithivMLmods : @prithivMLmods

The best dimensions and inference settings for optimal results are as follows: A resolution of 1280 x 832 with a 3:2 aspect ratio is recommended for the best quality, while 1024 x 1024 with a 1:1 aspect ratio serves as the default option. For inference, the recommended number of steps ranges between 30 and 35 to achieve optimal output.
ZennyKenny 
posted an update 10 days ago
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548
Phew, maybe a little dark, but I've submitted my second dataset to the Reasoning Datasets Competition: ZennyKenny/tactical-military-reasoning-v.1.0

I'd be interested to hear the community's thoughts on the applications of AI in the military. Especially in the wargaming space.

This is something that feels inevitable (and realistically, probably already in progress). Doesn't it make sense for us to have an understanding of the mechanics of such processes? Surely they will never be open source.
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burtenshaw 
posted an update 11 days ago
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2259
The rebooted LLM course starts today with an overhauled chapter 1 on Transformers:

👉 Follow the org to join the course: huggingface-course

We’re starting from the foundations of modern generative AI by looking at transformers. This chapter is expanded in depth and features so contains new material like:

FREE and CERTIFIED exam on fundamentals of transformers
deeper exploration of transformer architectures and attention mechanisms
end -to-end exploration of inference strategies for prefill and decode steps

The course has leveled up in complexity and depth, so this a great time to join in if you want to build you own AI models.
prithivMLmods 
posted an update 11 days ago
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1180
Dropping the domain-specific downstream image classification content moderation models, including the anime image type classification, GeoSceneNet, indoor-outdoor scene classification, and black-and-white vs. colored image classification models, along with the datasets. 🔥

╰┈➤Models :
+ GeoSceneNet : prithivMLmods/Multilabel-GeoSceneNet
+ IndoorOutdoorNet : prithivMLmods/IndoorOutdoorNet
+ B&W vs Colored : prithivMLmods/BnW-vs-Colored-Detection
+ Anime Image Type : prithivMLmods/Anime-Classification-v1.0
+ Multilabel Portrait : prithivMLmods/Multilabel-Portrait-SigLIP2

╰┈➤Datasets :
- GeoSceneNet : prithivMLmods/Multilabel-GeoSceneNet-16K
- IndoorOutdoorNet : prithivMLmods/IndoorOutdoorNet-20K
- BnW vs Colored : prithivMLmods/BnW-vs-Colored-10K
- Multilabel Portrait : prithivMLmods/Multilabel-Portrait-18K

╰┈➤Collections :
> Multilabel Image Classification Datasets : prithivMLmods/multilabel-image-classification-datasets-6809aa64637f45d4c47fa6ca
> Model Collection : prithivMLmods/siglip2-content-filters-models-v2-68053a958c42ef17a3a3f4d1

Note: The anime scene type dataset is not mentioned in the list because it is private and only accessible to members of the DeepGHS organization.

For raw ZIP files or more information about the datasets, visit: https://www.kaggle.com/prithivsakthiur/datasets
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fdaudens 
posted an update 12 days ago
sayakpaul 
authored a paper 12 days ago
davidberenstein1957 
posted an update 12 days ago
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2156
🔥 Announcing FLUX-Juiced: The Fastest Image Generation Endpoint (2.6x faster)!

Optimisations are widely applied and can reduce inference time, but their impact on quality often remains unclear, so we decided to challenge the status quo and create our own optimised version of FLUX.1[dev] called FLUX-juiced.

Blog: https://huggingface.co/blog/PrunaAI/flux-fastest-image-generation-endpoint
davanstrien 
posted an update 12 days ago
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1917
Came across a very nice submission from @marcodsn for the reasoning datasets competition (https://huggingface.co/blog/bespokelabs/reasoning-datasets-competition).

The dataset distils reasoning chains from arXiv research papers in biology and economics. Some nice features of the dataset:

- Extracts both the logical structure AND researcher intuition from academic papers
- Adopts the persona of researchers "before experiments" to capture exploratory thinking
- Provides multi-short and single-long reasoning formats with token budgets - Shows 7.2% improvement on MMLU-Pro Economics when fine-tuning a 3B model

It's created using the Curator framework with plans to scale across more scientific domains and incorporate multi-modal reasoning with charts and mathematics.

I personally am very excited about datasets like this, which involve creativity in their creation and don't just rely on $$$ to produce a big dataset with little novelty.

Dataset can be found here: marcodsn/academic-chains (give it a like!)
davidberenstein1957 
posted an update 17 days ago
prithivMLmods 
posted an update 18 days ago
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Dropping an entire collection of Style Intermixing Adapters on StrangerZone HF — including Realism, Anime, Sketch, Texture-Rich 3D Experimentals, Automotive Concept Images, and LoRA models based on Flux.1, SD 3.5 Turbo/Large, Stable Diffusion XL 🎨

╰┈➤Collection :
➜ sketch : strangerzonehf/sketch-fav-675ba869c7ceaec7e652ee1c
➜ sketch2 : strangerzonehf/q-series-sketch-678e3503bf3a661758429717
➜ automotive : strangerzonehf/automotive-3d-675bb31a491d8c264d45d843
➜ texture 3d : strangerzonehf/flux-3dxl-engine-674833c14a001d5b1fdb5139
➜ super 3d : strangerzonehf/super-3d-engine-6743231d69f496df97addd2b
➜ style mix : strangerzonehf/mixer-engine-673582c9c5939d8aa5bf9533
➜ realism : strangerzonehf/realism-engine-67343495b6daf0fbdb904cc1

╰┈➤The Entire Collection :
➜ flux.1 : prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
➜ flux-ultimate-lora-collection : strangerzonehf/Flux-Ultimate-LoRA-Collection
➜ sd 3.5 large / turbo : prithivMLmods/sd-35-large-lora-671b39d7bc2e7f71a446b163
➜ sdxl : prithivMLmods/sdxl-dev-models-667803a6d5ac75b59110e527

╰┈➤Pages :
➜ page 1: strangerzonehf
➜ page 2: @prithivMLmods
➜ demo : prithivMLmods/FLUX-LoRA-DLC

.🤗