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lewtunย  authored a paper 30 days ago
SmolVLM: Redefining small and efficient multimodal models
lewtunย  authored a paper about 2 months ago
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning
wannaphongย  authored a paper 3 months ago
Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs
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OWG's activity

prithivMLmodsย 
posted an update about 21 hours ago
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955
Well, hereโ€™s the updated version with the 20,000+ entry sampled dataset for Watermark Filter Content Moderation models incl. [Food25, Weather, Watermark, Marathi/Hindi Sign Language Detection], post-trained from the base models: sigLip2 patch16 224 โ€” now with mixed aspect ratios for better performance and reduced misclassification. ๐Ÿ”ฅ

Models :
โžฎ Watermark-Detection : prithivMLmods/Watermark-Detection-SigLIP2
โŒจ๏ธŽ Watermark Detection & Batch Image Processing Experimentals, Colab Notebook : https://colab.research.google.com/drive/1mlQrSsSjkGimUt0VyRi3SoWMv8OMyvw3?usp=drive_link
โžฎ Weather-Image-Classification : prithivMLmods/Weather-Image-Classification
โžฎ TurkishFoods-25 : prithivMLmods/TurkishFoods-25
โžฎ Marathi-Sign-Language-Detection : prithivMLmods/Marathi-Sign-Language-Detection
โžฎ Hindi-Sign-Language-Detection : prithivMLmods/Hindi-Sign-Language-Detection

Datasets :
Watermark : qwertyforce/scenery_watermarks
Weather : prithivMLmods/WeatherNet-05-18039
Turkish Foods 25 : yunusserhat/TurkishFoods-25
Marathi Sign Language : VinayHajare/Marathi-Sign-Language
Hindi Sign Language : Vedant3907/Hindi-Sign-Language-Dataset

Collection : prithivMLmods/content-filters-siglip2-vit-68197e3357d4de18fb3b4d2b
prithivMLmodsย 
posted an update 4 days ago
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959
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. ๐Ÿฅณ

Models [ โŒ— ]

> 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.
mkluczekย 
posted an update 7 days ago
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Expansion of Global and Dense Open Embeddings Dataset of Earth ๐ŸŒ

We updated our previous embeddings release with three models MMEarth and DeCUR-S2, DeCUR-S1 of the Major TOM embeddings dataset, developed in collaboration with CloudFerro S.A. asterisk labs and ฮฆ-lab, European Space Agency - ESA. Together with @mikonvergence , Jฤ™drzej S. Bojanowski, we extend the open-access collection of open dataset of Copernicus embeddings built at global scale, providing dense coverage across the entire acquisition area of Sentinel-1 and Sentinel-2 sensors.

Total embedding resources after the update:
- 51 TB of AI-embeddings generated from processed Sentinel data,
- over 40 billion embedding vectors,
- processing of 147 TB of raw satellite data,
- analysis covering more than 15 million Sentinel-1 and Sentinel-2 scenes and more than 16 trillion pixels.

This project delivers open and free vectorized expansions of Major TOM datasets available on CREODIAS and Hugging Face, setting a new standard for embedding releases and enabling lightweight, scalable ingestion of Earth Observation (EO) data for countless applications.

Datasets:
Major-TOM/Core-S2L2A-MMEarth
Major-TOM/Core-S2L1C-DeCUR
Major-TOM/Core-S1RTC-DeCUR


#EarthObservation #AI #CloudFerro #asterisklabs #ESA
shivalikasinghย 
authored a paper 8 days ago
prithivMLmodsย 
posted an update 8 days ago
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1786
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 : ๐Ÿค—

+ 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
Aurelien-Morganย 
posted an update 10 days ago
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3107
The Almighty function-caller

How would you like to build smart GenAi infrastructure ?
Give extensive tools memory to your edge agentic system,
And optimize the resources it takes to run yet a high-performance set of agents ?

We came up with a novel approach to function-calling at scale for smart companies and corporate-grade use-cases.

Read our full-fledged blog article on this here on Hugging Face :
https://huggingface.co/blog/Aurelien-Morgan/the-almighty-function-caller
Aurelien-Morganย 
posted an update 11 days ago
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652
retrain-pipelines 0.1.2 finally dropped. It comes with a hot Hugging Face Hub integration. Go check it out. We have 2 articles about it coming up. One already fully written so, be on the lookout !
@retrain-pipelines

Also, I'll be volunteering at GOSIM AI Paris 2025. If you're interested in chatting, hmu.
prithivMLmodsย 
posted an update 12 days ago
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2194
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. ๐Ÿฅณ

โ•ฐโ”ˆโžคDemo : prithivMLmods/FLUX-LoRA-DLC2 & prithivMLmods/FLUX-LoRA-DLC

โ•ฐโ”ˆโžค 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

โ•ฐโ”ˆโžค 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.
prithivMLmodsย 
posted an update 14 days ago
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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. ๐Ÿ”ฅ

โ•ฐโ”ˆโžคModels :
+ 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

โ•ฐโ”ˆโžคDatasets :
- GeoSceneNet : prithivMLmods/Multilabel-GeoSceneNet-16K
- IndoorOutdoorNet : prithivMLmods/IndoorOutdoorNet-20K
- BnW vs Colored : prithivMLmods/BnW-vs-Colored-10K
- Multilabel Portrait : prithivMLmods/Multilabel-Portrait-18K

โ•ฐโ”ˆโžคCollections :
> 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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prithivMLmodsย 
posted an update 20 days ago
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Dropping an entire collection of Style Intermixing Adapters on StrangerZone HF โ€” 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 ๐ŸŽจ

โ•ฐโ”ˆโžคCollection :
โžœ sketch : strangerzonehf/sketch-fav-675ba869c7ceaec7e652ee1c
โžœ sketch2 : strangerzonehf/q-series-sketch-678e3503bf3a661758429717
โžœ automotive : strangerzonehf/automotive-3d-675bb31a491d8c264d45d843
โžœ texture 3d : strangerzonehf/flux-3dxl-engine-674833c14a001d5b1fdb5139
โžœ super 3d : strangerzonehf/super-3d-engine-6743231d69f496df97addd2b
โžœ style mix : strangerzonehf/mixer-engine-673582c9c5939d8aa5bf9533
โžœ realism : strangerzonehf/realism-engine-67343495b6daf0fbdb904cc1

โ•ฐโ”ˆโžคThe Entire Collection :
โžœ flux.1 : prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
โžœ flux-ultimate-lora-collection : strangerzonehf/Flux-Ultimate-LoRA-Collection
โžœ sd 3.5 large / turbo : prithivMLmods/sd-35-large-lora-671b39d7bc2e7f71a446b163
โžœ sdxl : prithivMLmods/sdxl-dev-models-667803a6d5ac75b59110e527

โ•ฐโ”ˆโžคPages :
โžœ page 1: strangerzonehf
โžœ page 2: @prithivMLmods
โžœ demo : prithivMLmods/FLUX-LoRA-DLC

.๐Ÿค—
prithivMLmodsย 
posted an update 22 days ago
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Try out the demo for Multimodal OCR featuring the implementation of models including RolmOCR and Qwen2VL OCR. The use case showcases image-text-to-text conversion and video understanding support for the RolmOCR model ! ๐Ÿš€

๐Ÿค—Multimodal OCR Space : prithivMLmods/Multimodal-OCR

๐Ÿ“ฆThe models implemented in this Space are:
+ Qwen2VL OCR : prithivMLmods/Qwen2-VL-OCR-2B-Instruct [ or ]
+ Qwen2VL OCR2 : prithivMLmods/Qwen2-VL-OCR2-2B-Instruct
+ RolmOCR : reducto/RolmOCR

Qwen2VL OCR supports only image-text-to-text in the space.
prithivMLmodsย 
posted an update about 1 month ago
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Loaded some domain-specific downstream image classification content moderation models, which is essentially the practice of monitoring and filtering user-generated content on platforms, based on SigLIP-2 Base Patch16 with newly initialized trainable parameters. ๐Ÿฅ 

+ Age-Classification-SigLIP2 : prithivMLmods/Age-Classification-SigLIP2
[ Age range classification from 0 to 65+ years ]
+ Facial-Emotion-Detection-SigLIP2 : prithivMLmods/Facial-Emotion-Detection-SigLIP2
[ Designed to classify different facial emotions ]
+ Hand-Gesture-2-Robot : prithivMLmods/Hand-Gesture-2-Robot
[ Human Hand Gesture Classification for Robot Control ]
+ Mature-Content-Detection : prithivMLmods/Mature-Content-Detection
[ Mature [adult] or neutral content categories ]
+ Vit-Mature-Content-Detection : prithivMLmods/Vit-Mature-Content-Detection
[ Mature [adult] or neutral content categories ft. ViT]
+ Human-Action-Recognition : prithivMLmods/Human-Action-Recognition
[ Human actions including clapping, sitting, running, and more ]
+ Mirage-Photo-Classifier : prithivMLmods/Mirage-Photo-Classifier
[ Whether an image is real or AI-generated (fake) ]
+ Food-101-93M : prithivMLmods/Food-101-93M
[ Classify food images into one of 101 popular dishes ]
+ Hand-Gesture-19 : prithivMLmods/Hand-Gesture-19
[ Classify hand gesture images into different categories ]
+ Trash-Net : prithivMLmods/Trash-Net
[ Classification of trash into six distinct categories ]
+ Gender-Classifier-Mini : prithivMLmods/Gender-Classifier-Mini
[ Classify images based on gender [Male / Female] ]

๐ŸŽกCollections :

+ SigLIP2 Content Filters : https://huggingface.co/collections/prithivMLmods/siglip2-content-filters-models-67f001055ec2bed56ca41f6d
AtAndDevย 
posted an update about 1 month ago
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Llama 4 is out...
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prithivMLmodsย 
posted an update about 1 month ago
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ChatGPT-4oโ€™s image generation goes wild for a weekโ€”featuring everything from Studio Ghibli-style art and image colorization to style intermixing. Here are some examples showcasing the generation of highly detailed images from freestyle design templates. Want to know more? Check out the blog ๐Ÿš€

๐Ÿ”—Blog : https://huggingface.co/blog/prithivMLmods/chatgpt-4o-image-gen
prithivMLmodsย 
posted an update about 1 month ago
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Luna, the single-speaker text-to-speech model, features a Radio & Atcosim-style sound with a female voice. It offers authentic radio podcast noise and empathetic speech generation, fine-tuned based on Orpheus's Llama-based speech generation state-of-the-art model. ๐ŸŽ™๏ธ

+ Model : prithivMLmods/Llama-3B-Mono-Luna
+ Collection : prithivMLmods/clean-radio-mono-voice-67e76fe1b3a87cc3bccef803
+ Reference ft : https://github.com/canopyai/Orpheus-TTS
+ Base Model : canopylabs/orpheus-3b-0.1-ft

I also tried some other clean-voice single-speaker models based on Orpheus. If you're interested, check out the collection.

๐Ÿ”‰Try the Mono Luna demo here: http://colab.research.google.com/drive/1K0AAIOKDE5XE0znxXaiiUJvPSpFveteK
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Aurelien-Morganย 
posted an update about 1 month ago
prithivMLmodsย 
posted an update about 1 month ago
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Dropping some new Journey Art and Realism adapters for Flux.1-Dev, including Thematic Arts, 2021 Memory Adapters, Thread of Art, Black of Art, and more. For more details, visit the model card on Stranger Zone HF ๐Ÿค—

+ Black-of-Art-Flux : strangerzonehf/Black-of-Art-Flux
+ Thread-of-Art-Flux : strangerzonehf/Thread-of-Art-Flux
+ 2021-Art-Flux : strangerzonehf/2021-Art-Flux
+ 3d-Station-Toon : strangerzonehf/3d-Station-Toon
+ New-Journey-Art-Flux : strangerzonehf/New-Journey-Art-Flux
+ Casual-Pencil-Pro : strangerzonehf/Casual-Pencil-Pro
+ Realism-H6-Flux : strangerzonehf/Realism-H6-Flux

- Repository Page : strangerzonehf

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.
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prithivMLmodsย 
posted an update about 1 month ago
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Dropping Downstream tasks using newly initialized parameters and weights ([classifier.bias & weights]) support domain-specific ๐—ถ๐—บ๐—ฎ๐—ด๐—ฒ ๐—ฐ๐—น๐—ฎ๐˜€๐˜€๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป. Based on siglip2-base-patch16-224 and DomainNet (single-domain, multi-source adaptation), with Fashion-MNIST & More for experimental testing. ๐Ÿงคโ˜„๏ธ

Fashion-Mnist : prithivMLmods/Fashion-Mnist-SigLIP2
Mnist-Digits : prithivMLmods/Mnist-Digits-SigLIP2
Multisource-121 : prithivMLmods/Multisource-121-DomainNet
Painting-126 : prithivMLmods/Painting-126-DomainNet
Sketch-126 : prithivMLmods/Sketch-126-DomainNet
Clipart-126 : prithivMLmods/Clipart-126-DomainNet

Models are trained with different parameter settings for experimental purposes only, with the intent of further development. Refer to the model page below for instructions on running it with Transformers ๐Ÿค—.

Collection : prithivMLmods/domainnet-0324-67e0e3c934c03cc40c6c8782

Citations : SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 & Moment Matching for Multi-Source Domain Adaptation : https://arxiv.org/pdf/1812.01754
louisbrulenaudetย 
posted an update about 2 months ago
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Iโ€™ve just released logfire-callback on PyPI, designed to facilitate monitoring of Hugging Face Transformer training loops using Pydantic Logfire ๐Ÿค—

The callback will automatically log training start with configuration parameters, periodic metrics and training completion โฑ๏ธ

Install the package using pip:
pip install logfire-callback

First, ensure you have a Logfire API token and set it as an environment variable:
export LOGFIRE_TOKEN=your_logfire_token

Then use the callback in your training code:
from transformers import Trainer, TrainingArguments
from logfire_callback import LogfireCallback

# Initialize your model, dataset, etc.

training_args = TrainingArguments(
    output_dir="./results",
    num_train_epochs=3,
    # ... other training arguments
)

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset,
    callbacks=[LogfireCallback()]  # Add the Logfire callback here
)

trainer.train()

If you have any feedback, please reach out at @louisbrulenaudet
prithivMLmodsย 
posted an update about 2 months ago
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Play with Orpheus TTS, a Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been fine-tuned to deliver human-level speech synthesis ๐Ÿ”ฅ๐Ÿ—ฃ๏ธ

๐Ÿ‘‰GitHub [ Demo ] : https://github.com/PRITHIVSAKTHIUR/Orpheus-TTS-Edge

Demo supporting both text-to-speech and text-to-llm responses in speech.

> voice: tara, dan, emma, josh
> emotion: <laugh>, <chuckle>, <sigh>, <cough>, <sniffle>, <groan>, <yawn>, <gasp>.

๐Ÿฅ Orpheus-3b-0.1-ft
Model Page: canopylabs/orpheus-3b-0.1-ft

๐Ÿฅ Orpheus-3b-0.1-ft
Colab Inference Notebook: https://colab.research.google.com/drive/1KhXT56UePPUHhqitJNUxq63k-pQomz3N?usp=sharing

๐Ÿฅ Finetune [ orpheus-3b-0.1-pretrained ]
Resource: https://github.com/canopyai/Orpheus-TTS/tree/main/finetune

๐Ÿฅ Model-releases:
https://canopylabs.ai/model-releases
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