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The timm Leaderboard
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Display and analyze PyTorch Image Models leaderboard
Youssef Boulaouane
joseph-bou
AI & ML interests
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liked
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9 days ago
timm/leaderboard
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14 days ago
Qwen/QwQ-32B
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csabakecskemeti's
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23 days ago
Testing Training on AMD/ROCm the first time!
I've got my hands on an AMD Instinct MI100. It's about the same price used as a V100 but on paper has more TOPS (V100 14TOPS vs MI100 23TOPS) also the HBM has faster clock so the memory bandwidth is 1.2TB/s.
For quantized inference it's a beast (MI50 was also surprisingly fast)
For LORA training with this quick test I could not make the bnb config works so I'm running the FT on the fill size model.
Will share all the install, setup and setting I've learned in a blog post, together with the cooling shroud 3D design.
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joseph-bou's activity
liked
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Space
9 days ago
liked
a
model
14 days ago
reacted to
csabakecskemeti's
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23 days ago
Post
2763
Testing Training on AMD/ROCm the first time!
I've got my hands on an AMD Instinct MI100. It's about the same price used as a V100 but on paper has more TOPS (V100 14TOPS vs MI100 23TOPS) also the HBM has faster clock so the memory bandwidth is 1.2TB/s.
For quantized inference it's a beast (MI50 was also surprisingly fast)
For LORA training with this quick test I could not make the bnb config works so I'm running the FT on the fill size model.
Will share all the install, setup and setting I've learned in a blog post, together with the cooling shroud 3D design.
I've got my hands on an AMD Instinct MI100. It's about the same price used as a V100 but on paper has more TOPS (V100 14TOPS vs MI100 23TOPS) also the HBM has faster clock so the memory bandwidth is 1.2TB/s.
For quantized inference it's a beast (MI50 was also surprisingly fast)
For LORA training with this quick test I could not make the bnb config works so I'm running the FT on the fill size model.
Will share all the install, setup and setting I've learned in a blog post, together with the cooling shroud 3D design.
- 8 replies
reacted to
lysandre's
post with 🚀
24 days ago
Post
5716
SmolVLM-2 and SigLIP-2 are now part of
They're added on top of the v4.49.0 release, and can be installed from the following tags:
This marks a new beginning for the release process of transformers. For the past five years, we've been doing monthly releases featuring many models (v4.49.0, the latest release, features 9 new architectures).
Starting with SmolVLM-2 & SigLIP2, we'll now additionally release tags supporting new models on a stable branch. These models are therefore directly available for use by installing from the tag itself. These tags will continue to be updated with fixes applied to these models.
Going forward, continue expecting software releases following semantic versioning: v4.50.0 will have ~10 new architectures compared to v4.49.0, as well as a myriad of new features, improvements and bug fixes. Accompanying these software releases, we'll release tags offering brand new models as fast as possible, to make them accessible to all immediately.
transformers in dedicated releases!They're added on top of the v4.49.0 release, and can be installed from the following tags:
v4.49.0-SmolVLM-2 and v4.49.0-SigLIP-2.This marks a new beginning for the release process of transformers. For the past five years, we've been doing monthly releases featuring many models (v4.49.0, the latest release, features 9 new architectures).
Starting with SmolVLM-2 & SigLIP2, we'll now additionally release tags supporting new models on a stable branch. These models are therefore directly available for use by installing from the tag itself. These tags will continue to be updated with fixes applied to these models.
Going forward, continue expecting software releases following semantic versioning: v4.50.0 will have ~10 new architectures compared to v4.49.0, as well as a myriad of new features, improvements and bug fixes. Accompanying these software releases, we'll release tags offering brand new models as fast as possible, to make them accessible to all immediately.
- 1 reply
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28 days ago
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28 days ago
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28 days ago
Article
PaliGemma 2 Mix - New Instruction Vision Language Models by Google
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reacted to
merve's
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28 days ago
Post
6216
Google just released PaliGemma 2 Mix: new versatile instruction vision language models 🔥
> Three new models: 3B, 10B, 28B with res 224, 448 💙
> Can do vision language tasks with open-ended prompts, understand documents, and segment or detect anything 🤯
Read more https://huggingface.co/blog/paligemma2mix
Try the demo google/paligemma2-10b-mix
All models are here google/paligemma-2-mix-67ac6a251aaf3ee73679dcc4
> Three new models: 3B, 10B, 28B with res 224, 448 💙
> Can do vision language tasks with open-ended prompts, understand documents, and segment or detect anything 🤯
Read more https://huggingface.co/blog/paligemma2mix
Try the demo google/paligemma2-10b-mix
All models are here google/paligemma-2-mix-67ac6a251aaf3ee73679dcc4
liked
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about 1 month ago
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ginipick's
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about 1 month ago
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5897
Gini's AI Spaces: Everything You Need for Visual Content Creation!
Hello! ✨ Let me introduce Gini’s 5 AI Spaces that effortlessly generate various styles of visual content.
Each Space leverages Diffusers and Gradio, so you can create stunning images in just a few clicks!
1) Flowchart
Features: Hand-drawn style flowcharts for workflows or business processes
Use Cases: Software release pipelines, data pipelines, corporate workflows
Benefits: Clear stage-by-stage structure, simple icon usage
ginigen/Flowchart
2) Infographic
Features: Visually appealing infographics that communicate data or statistics
Use Cases: Global energy charts, startup growth metrics, health tips and more
Benefits: Eye-catching icons and layouts, perfect for storytelling at a glance
ginigen/Infographic
3) Mockup
Features: Sketch-style wireframes or UX mockups for apps/websites
Use Cases: Mobile login flows, dashboards, e-commerce site layouts
Benefits: Rapid prototyping of early design ideas, perfect for storyboarding
ginigen/Mockup
4) Diagram
Features: Educational diagrams (science, biology, geography, etc.)
Use Cases: Water cycle, photosynthesis, chemical reactions, human anatomy
Benefits: Vibrant, friendly illustrations, ideal for student-friendly materials
ginigen/Diagram
5) Design
Features: Product/industrial design concepts (coffee machines, smartphones, etc.)
Use Cases: Prototyping, concept car interiors, high-tech product sketches
Benefits: From 3D render-like visuals to simple sketches, unleash your creativity!
ginigen/Design
Click any link above and let AI spark your imagination. Enjoy a fun and productive creative process! 🚀✨
Hello! ✨ Let me introduce Gini’s 5 AI Spaces that effortlessly generate various styles of visual content.
Each Space leverages Diffusers and Gradio, so you can create stunning images in just a few clicks!
1) Flowchart
Features: Hand-drawn style flowcharts for workflows or business processes
Use Cases: Software release pipelines, data pipelines, corporate workflows
Benefits: Clear stage-by-stage structure, simple icon usage
ginigen/Flowchart
2) Infographic
Features: Visually appealing infographics that communicate data or statistics
Use Cases: Global energy charts, startup growth metrics, health tips and more
Benefits: Eye-catching icons and layouts, perfect for storytelling at a glance
ginigen/Infographic
3) Mockup
Features: Sketch-style wireframes or UX mockups for apps/websites
Use Cases: Mobile login flows, dashboards, e-commerce site layouts
Benefits: Rapid prototyping of early design ideas, perfect for storyboarding
ginigen/Mockup
4) Diagram
Features: Educational diagrams (science, biology, geography, etc.)
Use Cases: Water cycle, photosynthesis, chemical reactions, human anatomy
Benefits: Vibrant, friendly illustrations, ideal for student-friendly materials
ginigen/Diagram
5) Design
Features: Product/industrial design concepts (coffee machines, smartphones, etc.)
Use Cases: Prototyping, concept car interiors, high-tech product sketches
Benefits: From 3D render-like visuals to simple sketches, unleash your creativity!
ginigen/Design
Click any link above and let AI spark your imagination. Enjoy a fun and productive creative process! 🚀✨
reacted to
Duskfallcrew's
post with 👀
about 1 month ago
Post
542
I have too many articles I need to post now that i've left a certain site xD.
I'm not copying ALL my articles over, just the really cool ones that I got to write because I have a design degree that means nothing in ML, and while I can't really give ML research a go totally? I can at least apply my "I CAN MAKE PRETTY PICTURES" knowledge to some academic theory! Watch this space, i'll be porting my Design Theory for AI articles over soon! <3
I'm not copying ALL my articles over, just the really cool ones that I got to write because I have a design degree that means nothing in ML, and while I can't really give ML research a go totally? I can at least apply my "I CAN MAKE PRETTY PICTURES" knowledge to some academic theory! Watch this space, i'll be porting my Design Theory for AI articles over soon! <3
reacted to
DawnC's
post with ❤️
about 1 month ago
Post
1226
🌟 PawMatchAI: Making Breed Selection More Intuitive! 🐕
Excited to share the latest breakthrough in my AI-powered companion for finding your perfect furry friend! I've made significant improvements in breed recognition through innovative learning techniques!
✨ What's New?
🎯 Major Recognition Enhancement:
- Implemented ICARL with advanced knowledge distillation, inspired by human learning processes
- Dramatically improved recognition of challenging breeds like Havanese
- Created an intelligent learning system that mimics how expert teachers adapt their teaching style
- Added smart feature protection to maintain recognition accuracy across all breeds
🔬 Technical Innovations:
- Enhanced breed recognition through advanced morphological feature analysis
- Implemented sophisticated feature extraction system for body proportions, head features, tail structure, fur texture, and color patterns
- Added intelligent attention mechanism for dynamic feature focus
- Improved multi-dog detection with enhanced spatial analysis
🎯 Key Features:
- Smart breed recognition powered by biomimetic AI architecture
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Taking inspiration from both AI technology and natural learning processes, this project continues to evolve in making breed selection more accessible while pushing the boundaries of AI capabilities.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ fuel the continuous improvement of this project!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision #TechForLife #ICARL #KnowledgeDistillation
Excited to share the latest breakthrough in my AI-powered companion for finding your perfect furry friend! I've made significant improvements in breed recognition through innovative learning techniques!
✨ What's New?
🎯 Major Recognition Enhancement:
- Implemented ICARL with advanced knowledge distillation, inspired by human learning processes
- Dramatically improved recognition of challenging breeds like Havanese
- Created an intelligent learning system that mimics how expert teachers adapt their teaching style
- Added smart feature protection to maintain recognition accuracy across all breeds
🔬 Technical Innovations:
- Enhanced breed recognition through advanced morphological feature analysis
- Implemented sophisticated feature extraction system for body proportions, head features, tail structure, fur texture, and color patterns
- Added intelligent attention mechanism for dynamic feature focus
- Improved multi-dog detection with enhanced spatial analysis
🎯 Key Features:
- Smart breed recognition powered by biomimetic AI architecture
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Taking inspiration from both AI technology and natural learning processes, this project continues to evolve in making breed selection more accessible while pushing the boundaries of AI capabilities.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ fuel the continuous improvement of this project!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision #TechForLife #ICARL #KnowledgeDistillation
- 10 replies
liked
2
models
about 2 months ago
reacted to
rwightman's
post with 👍
about 2 months ago
Post
1452
I re-worked the JuptyerLab Space template recently. It's optimized for
timm use, but will work great with transformers and other libs. Updated the base image, Python 3.12, Pillow-SIMD before better CPU use with image preprocessing, and made a number of other tweaks. From the Jupyter launcher you can run the terminal and setup a timm environment in moments with setup_timm_dev or setup_timm_scripts helpers. Give it a try,
timm/jupyterlab-timm
liked
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Spaces
2 months ago
upvoted
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2 months ago
Article
Timm ❤️ Transformers: Use any timm model with transformers
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