Post
711
Where gone streamlit in huggingface?
- 2 replies
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prithivMLmods
posted
an
update
2 days ago
Post
1686
Got access to Google's all-new Gemini Diffusion a state-of-the-art text diffusion model. It delivers the performance of Gemini 2.0 Flash-Lite at 5x the speed, generating over 1000 tokens in a fraction of a second and producing impressive results. Below are some initial outputs generated using the model. ♊🔥
Gemini Diffusion Playground ✦ : https://deepmind.google.com/frontiers/gemini-diffusion
Get Access Here : https://docs.google.com/forms/d/1aLm6J13tAkq4v4qwGR3z35W2qWy7mHiiA0wGEpecooo/viewform?edit_requested=true
🔗 To know more, visit: https://deepmind.google/models/gemini-diffusion/
Gemini Diffusion Playground ✦ : https://deepmind.google.com/frontiers/gemini-diffusion
Get Access Here : https://docs.google.com/forms/d/1aLm6J13tAkq4v4qwGR3z35W2qWy7mHiiA0wGEpecooo/viewform?edit_requested=true
🔗 To know more, visit: https://deepmind.google/models/gemini-diffusion/
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- 1 reply
prithivMLmods
posted
an
update
4 days ago
Post
2137
The more optimized explicit content filters with lightweight 𝙜𝙪𝙖𝙧𝙙 models trained based on siglip2 patch16 512 and vit patch16 224 for illustration and explicit content classification for content moderation in social media, forums, and parental controls for safer browsing environments. this version fixes the issues in the previous release, which lacked sufficient resources. 🚀
⤷ Models :
→ siglip2 mini explicit content : prithivMLmods/siglip2-mini-explicit-content [recommended]
→ vit mini explicit content : prithivMLmods/vit-mini-explicit-content
⤷ Building image safety-guard models :
strangerguardhf
⤷ Datasets :
→ nsfw multidomain classification : strangerguardhf/NSFW-MultiDomain-Classification
→ nsfw multidomain classification v2.0 : strangerguardhf/NSFW-MultiDomain-Classification-v2.0
⤷ Collection :
→ Updated Versions [05192025] : prithivMLmods/explicit-content-filters-682aaa4733e378561925ca2b
→ Previous Versions : prithivMLmods/siglip2-content-filters-042025-final-680fe4aa1a9d589bf2c915ff
Find a collections inside the collection.👆
To know more about it, visit the model card of the respective model.
⤷ Models :
→ siglip2 mini explicit content : prithivMLmods/siglip2-mini-explicit-content [recommended]
→ vit mini explicit content : prithivMLmods/vit-mini-explicit-content
⤷ Building image safety-guard models :
strangerguardhf
⤷ Datasets :
→ nsfw multidomain classification : strangerguardhf/NSFW-MultiDomain-Classification
→ nsfw multidomain classification v2.0 : strangerguardhf/NSFW-MultiDomain-Classification-v2.0
⤷ Collection :
→ Updated Versions [05192025] : prithivMLmods/explicit-content-filters-682aaa4733e378561925ca2b
→ Previous Versions : prithivMLmods/siglip2-content-filters-042025-final-680fe4aa1a9d589bf2c915ff
Find a collections inside the collection.👆
To know more about it, visit the model card of the respective model.
- 1 reply
juliehunter
updated
a
dataset
7 days ago
Aurelien-Morgan
posted
an
update
7 days ago
Post
366
Hey, I'll be presenting
@retrain-pipelines
and almighty function-calling at the Hugging Face Paris HQ, you guys.
Monday evening. Lightning-talk style. With AI Tinkerers.
Come hang !
https://paris.aitinkerers.org/p/ai-tinkerers-paris-ai21-labs-takeover-on-may-19th
https://huggingface.co/blog/Aurelien-Morgan/the-almighty-function-caller
Monday evening. Lightning-talk style. With AI Tinkerers.
Come hang !
https://paris.aitinkerers.org/p/ai-tinkerers-paris-ai21-labs-takeover-on-may-19th
https://huggingface.co/blog/Aurelien-Morgan/the-almighty-function-caller
prithivMLmods
posted
an
update
8 days ago
Post
2627
Models for detecting images generated by diffusion models (Flux.1, SDXL, ..) are trained or fine-tuned using image classification models for content moderation. These models use datasets available on the Hub. For identifying AI-generated images or moderating visual content, the recommended model is OpenSDI-Flux.1-SigLIP2.😺🧨
Models : prithivMLmods/OpenSDI-Flux.1-SigLIP2 [Best approach for AI [Diffusion Generated] vs. real image classification] prithivMLmods/OpenSDI-SD2.1-SigLIP2 prithivMLmods/OpenSDI-SD3-SigLIP2 prithivMLmods/OpenSDI-SD1.5-SigLIP2 prithivMLmods/OpenSDI-SDXL-SigLIP2
Datasets : nebula/OpenSDI_test madebyollin/megalith-10m
Collection : prithivMLmods/opensdi-diffusion-generated-image-classification-682488a3a3e5be7083db3383
Find a collections inside the collection.👆
To know more about it, visit the model card of the respective model.
Models : prithivMLmods/OpenSDI-Flux.1-SigLIP2 [Best approach for AI [Diffusion Generated] vs. real image classification] prithivMLmods/OpenSDI-SD2.1-SigLIP2 prithivMLmods/OpenSDI-SD3-SigLIP2 prithivMLmods/OpenSDI-SD1.5-SigLIP2 prithivMLmods/OpenSDI-SDXL-SigLIP2
Datasets : nebula/OpenSDI_test madebyollin/megalith-10m
Collection : prithivMLmods/opensdi-diffusion-generated-image-classification-682488a3a3e5be7083db3383
Find a collections inside the collection.👆
To know more about it, visit the model card of the respective model.
Jeronymous
updated
a
dataset
9 days ago
prithivMLmods
posted
an
update
9 days ago
Post
1976
Dropping some image classification models for content moderation and classifiers trained with datasets available on the Hub. All are fine-tuned on the
🤗Models :
AI or Not : prithivMLmods/AIorNot-SigLIP2
Driver Drowsiness Detection : prithivMLmods/DOZE-GUARD-RLDD
Subset 10 ImageNet : prithivMLmods/IMAGENETTE
🥊Datasets :
+ competitions/aiornot
+ akahana/Driver-Drowsiness-Dataset
+ frgfm/imagenette
🔗Collection :
[The previous collection of models is also listed in the same collection, so you can find more models focused on image classification tasks.]
- prithivMLmods/multiclass-image-classification-05142025-68234c8010a9350a4d6739b5
Find a collections inside the collection.🤪👆
To know more about it, visit the model card of the respective model.
siglip2 backbone, (competitions AIOrNot, Imagenette, and Driver-Drowsiness). Models and datasets are listed below:🤗Models :
AI or Not : prithivMLmods/AIorNot-SigLIP2
Driver Drowsiness Detection : prithivMLmods/DOZE-GUARD-RLDD
Subset 10 ImageNet : prithivMLmods/IMAGENETTE
🥊Datasets :
+ competitions/aiornot
+ akahana/Driver-Drowsiness-Dataset
+ frgfm/imagenette
🔗Collection :
[The previous collection of models is also listed in the same collection, so you can find more models focused on image classification tasks.]
- prithivMLmods/multiclass-image-classification-05142025-68234c8010a9350a4d6739b5
Find a collections inside the collection.🤪👆
To know more about it, visit the model card of the respective model.
prithivMLmods
posted
an
update
13 days ago
Post
3485
Dropping some image classification models for content moderation, balancers, and classifiers trained on synthetic datasets—along with others based on datasets available on the Hub. Also loaded a few low-rank datasets for realistic gender portrait classification and document-type classifiers, all fine-tuned on the SigLIP-2 Patch-16 224 backbone. Models and datasets are listed below:
🤗Models & Datasets :
Realistic Gender Classification : prithivMLmods/Realistic-Gender-Classification
⎙ prithivMLmods/Realistic-Portrait-Gender-1024px
Document Type Detection : prithivMLmods/Document-Type-Detection
⎙ prithivMLmods/Document-Type-Detection
Face Mask Detection : prithivMLmods/Face-Mask-Detection
⎙ DamarJati/Face-Mask-Detection
Alzheimer Stage Classifier : prithivMLmods/Alzheimer-Stage-Classifier
⎙ SilpaCS/Augmented_alzheimer
Bone Fracture Detection : prithivMLmods/Bone-Fracture-Detection
⎙ Hemg/bone-fracture-detection
GiD Land Cover Classification : prithivMLmods/GiD-Land-Cover-Classification
⎙ jonathan-roberts1/GID
🤗Collection : prithivMLmods/siglip2-05102025-681c2b0e406f0740a993fc1c
To know more about it, visit the model card of the respective model.
🤗Models & Datasets :
Realistic Gender Classification : prithivMLmods/Realistic-Gender-Classification
⎙ prithivMLmods/Realistic-Portrait-Gender-1024px
Document Type Detection : prithivMLmods/Document-Type-Detection
⎙ prithivMLmods/Document-Type-Detection
Face Mask Detection : prithivMLmods/Face-Mask-Detection
⎙ DamarJati/Face-Mask-Detection
Alzheimer Stage Classifier : prithivMLmods/Alzheimer-Stage-Classifier
⎙ SilpaCS/Augmented_alzheimer
Bone Fracture Detection : prithivMLmods/Bone-Fracture-Detection
⎙ Hemg/bone-fracture-detection
GiD Land Cover Classification : prithivMLmods/GiD-Land-Cover-Classification
⎙ jonathan-roberts1/GID
🤗Collection : prithivMLmods/siglip2-05102025-681c2b0e406f0740a993fc1c
To know more about it, visit the model card of the respective model.
Post
1712
Haven't seen this posted anywhere - Llama-3.3-8B-Instruct is available on the new Llama API. Is this a new model or did someone mislabel Llama-3.1-8B?
- 1 reply
ZennyKenny
posted
an
update
15 days ago
Post
861
Community! 💡💡💡
It's the last day to submit your datasets for the Reasoning Datasets Competition: https://www.bespokelabs.ai/blog/reasoning-datasets-competition
Here are my submissions:
- ZennyKenny/synthetic_vc_financial_decisions_reasoning_dataset
- ZennyKenny/cosa-benchmark-dataset
- ZennyKenny/tactical-military-reasoning-v.1.0
- ZennyKenny/tron-dataset-v.1.0
Have a look and drop a ❤️ or comment! Check out the entire collection of submissions here: https://huggingface.co/datasets?other=reasoning-datasets-competition
It's the last day to submit your datasets for the Reasoning Datasets Competition: https://www.bespokelabs.ai/blog/reasoning-datasets-competition
Here are my submissions:
- ZennyKenny/synthetic_vc_financial_decisions_reasoning_dataset
- ZennyKenny/cosa-benchmark-dataset
- ZennyKenny/tactical-military-reasoning-v.1.0
- ZennyKenny/tron-dataset-v.1.0
Have a look and drop a ❤️ or comment! Check out the entire collection of submissions here: https://huggingface.co/datasets?other=reasoning-datasets-competition
prithivMLmods
posted
an
update
16 days ago
Post
3239
Well, here’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 — now with mixed aspect ratios for better performance and reduced misclassification. 🔥
Models :
➮ Watermark-Detection : prithivMLmods/Watermark-Detection-SigLIP2
⌨︎ Watermark Detection & Batch Image Processing Experimentals, Colab Notebook : https://colab.research.google.com/drive/1mlQrSsSjkGimUt0VyRi3SoWMv8OMyvw3?usp=drive_link
➮ Weather-Image-Classification : prithivMLmods/Weather-Image-Classification
➮ TurkishFoods-25 : prithivMLmods/TurkishFoods-25
➮ Marathi-Sign-Language-Detection : prithivMLmods/Marathi-Sign-Language-Detection
➮ 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
Models :
➮ Watermark-Detection : prithivMLmods/Watermark-Detection-SigLIP2
⌨︎ Watermark Detection & Batch Image Processing Experimentals, Colab Notebook : https://colab.research.google.com/drive/1mlQrSsSjkGimUt0VyRi3SoWMv8OMyvw3?usp=drive_link
➮ Weather-Image-Classification : prithivMLmods/Weather-Image-Classification
➮ TurkishFoods-25 : prithivMLmods/TurkishFoods-25
➮ Marathi-Sign-Language-Detection : prithivMLmods/Marathi-Sign-Language-Detection
➮ 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
ZennyKenny
posted
an
update
17 days ago
Post
3128
After hearing the news that Marc Andreessen thinks that the only job that is safe from AI replacement is venture capital: https://gizmodo.com/marc-andreessen-says-one-job-is-mostly-safe-from-ai-venture-capitalist-2000596506 🧠🧠🧠
The Reasoned Capital synthetic dataset suddenly feels much more topical: ZennyKenny/synthetic_vc_financial_decisions_reasoning_dataset 🔥🔥🔥
Really looking forward to potentially expanding this architecture and seeing how algorithmic clever investment truly is! 💰💰💰
The Reasoned Capital synthetic dataset suddenly feels much more topical: ZennyKenny/synthetic_vc_financial_decisions_reasoning_dataset 🔥🔥🔥
Really looking forward to potentially expanding this architecture and seeing how algorithmic clever investment truly is! 💰💰💰
Jeronymous
updated
a
model
18 days ago
ZennyKenny
posted
an
update
19 days ago
Post
3354
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.
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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- 2 replies
prithivMLmods
posted
an
update
19 days ago
Post
1152
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.
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.
Post
1579
PSA for anyone using
Both of these themes have been updated to fix some of the long-standing inconsistencies ever since the transition to Gradio v5. Textboxes are no longer bright green and
If your space is already using one of these themes, you just need to restart your space to get the latest version. No code changes needed.
Nymbo/Nymbo_Theme or Nymbo/Nymbo_Theme_5 in a Gradio space ~Both of these themes have been updated to fix some of the long-standing inconsistencies ever since the transition to Gradio v5. Textboxes are no longer bright green and
in-line code is readable now! Both themes are now visually identical across versions.If your space is already using one of these themes, you just need to restart your space to get the latest version. No code changes needed.
prithivMLmods
posted
an
update
23 days ago
Post
1925
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
- explicit content patch16 256 : prithivMLmods/siglip2-x256-explicit-content
- explicit content patch32 256 : prithivMLmods/siglip2-x256p32-explicit-content
> 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
+ 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
23 days ago
Post
1365
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. 🖖
@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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- 2 replies
Pclanglais
authored
a
paper
24 days ago