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FLUX.1 Kontext LoRA the Explorer
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edit images with Kontext and LoRAs
Tahir
TahirC
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kontext-community/FLUX.1-Kontext-portrait
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echo840/MonkeyOCR:License Clarification
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3 days ago
echo840/MonkeyOCR:Add LICENSE
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License Clarification
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#9 opened 21 days ago
by
rsingnn
Add LICENSE
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#15 opened 3 days ago
by
TahirC
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3 days ago
license must be Flux dev non commercial
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#1 opened 3 days ago
by
TahirC
reacted to
aiqtech's
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3 days ago
Post
2128
π₯ HuggingFace Heatmap Leaderboard
Visualizing AI ecosystem activity at a glance
aiqtech/Heatmap-Leaderboard
π― Introduction
A leaderboard that visualizes the vibrant HuggingFace community activity through heatmaps.
β¨ Key Features
π Real-time Tracking - Model/dataset/app releases from AI labs and developers
π Auto Ranking - Rankings based on activity over the past year
π¨ Responsive UI - Unique colors per organization, mobile optimized
β‘ Auto Updates - Hourly data refresh for latest information
π Major Participants
Big Tech: OpenAI, Google, Meta, Microsoft, Apple, NVIDIA
AI Startups: Anthropic, Mistral, Stability AI, Cohere, DeepSeek
Chinese Companies: Tencent, Baidu, ByteDance, Qwen
HuggingFace Official: HuggingFaceH4, HuggingFaceM4, lerobot, etc.
Active Developers: prithivMLmods, lllyasviel, multimodalart and many more
π Value
Trend Analysis π Real-time open source contribution insights
Inspiration πͺ Learn from other developers' activity patterns
Ecosystem Growth π± Visualize AI community development
@John6666 @Nymbo @MaziyarPanahi @prithivMLmods @fffiloni @gokaygokay @enzostvs @black-forest-labs @lllyasviel @briaai @multimodalart @unsloth @Xenova @mistralai @meta-llama @facebook @openai @Anthropic @google @allenai @apple @microsoft @nvidia @CohereLabs @ibm-granite @stabilityai @huggingface @OpenEvals @HuggingFaceTB @HuggingFaceH4 @HuggingFaceM4 @HuggingFaceFW @HuggingFaceFV @open-r1 @parler-tts @nanotron @lerobot @distilbert @kakaobrain @NCSOFT @upstage @moreh @LGAI-EXAONE @naver-hyperclovax @OnomaAIResearch @kakaocorp @Baidu @PaddlePaddle @tencent @BAAI @OpenGVLab @InternLM @Skywork @MiniMaxAI @stepfun-ai @ByteDance @Bytedance Seed @bytedance-research @openbmb @THUDM @rednote-hilab @deepseek-ai @Qwen @wan-ai @XiaomiMiMo @IndexTeam @agents-course
@Agents-MCP-Hackathon @akhaliq @alexnasa @Alibaba-NLP
@ArtificialAnalysis @bartowski @bibibi12345 @calcuis
@ChenDY @city96 @Comfy-Org @fancyfeast @fal @google
Visualizing AI ecosystem activity at a glance
aiqtech/Heatmap-Leaderboard
π― Introduction
A leaderboard that visualizes the vibrant HuggingFace community activity through heatmaps.
β¨ Key Features
π Real-time Tracking - Model/dataset/app releases from AI labs and developers
π Auto Ranking - Rankings based on activity over the past year
π¨ Responsive UI - Unique colors per organization, mobile optimized
β‘ Auto Updates - Hourly data refresh for latest information
π Major Participants
Big Tech: OpenAI, Google, Meta, Microsoft, Apple, NVIDIA
AI Startups: Anthropic, Mistral, Stability AI, Cohere, DeepSeek
Chinese Companies: Tencent, Baidu, ByteDance, Qwen
HuggingFace Official: HuggingFaceH4, HuggingFaceM4, lerobot, etc.
Active Developers: prithivMLmods, lllyasviel, multimodalart and many more
π Value
Trend Analysis π Real-time open source contribution insights
Inspiration πͺ Learn from other developers' activity patterns
Ecosystem Growth π± Visualize AI community development
@John6666 @Nymbo @MaziyarPanahi @prithivMLmods @fffiloni @gokaygokay @enzostvs @black-forest-labs @lllyasviel @briaai @multimodalart @unsloth @Xenova @mistralai @meta-llama @facebook @openai @Anthropic @google @allenai @apple @microsoft @nvidia @CohereLabs @ibm-granite @stabilityai @huggingface @OpenEvals @HuggingFaceTB @HuggingFaceH4 @HuggingFaceM4 @HuggingFaceFW @HuggingFaceFV @open-r1 @parler-tts @nanotron @lerobot @distilbert @kakaobrain @NCSOFT @upstage @moreh @LGAI-EXAONE @naver-hyperclovax @OnomaAIResearch @kakaocorp @Baidu @PaddlePaddle @tencent @BAAI @OpenGVLab @InternLM @Skywork @MiniMaxAI @stepfun-ai @ByteDance @Bytedance Seed @bytedance-research @openbmb @THUDM @rednote-hilab @deepseek-ai @Qwen @wan-ai @XiaomiMiMo @IndexTeam @agents-course
@Agents-MCP-Hackathon @akhaliq @alexnasa @Alibaba-NLP
@ArtificialAnalysis @bartowski @bibibi12345 @calcuis
@ChenDY @city96 @Comfy-Org @fancyfeast @fal @google
- 1 reply
Wrong Model license
1
#1 opened 6 days ago
by
TahirC
liked
a
model
13 days ago
liked
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Space
14 days ago
liked
a
model
14 days ago
upvoted
a
paper
19 days ago
liked
a
model
20 days ago
vllm implementation
#9 opened 21 days ago
by
TahirC
liked
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model
24 days ago
reacted to
MonsterMMORPG's
post with π₯
25 days ago
Post
2055
Ultimate ComfyUI & SwarmUI on RunPod Tutorial with Addition RTX 5000 Series GPUs & 1-Click to Setup : https://youtu.be/R02kPf9Y3_w
Tutorial Video : https://youtu.be/R02kPf9Y3_w
If you want to use ComfyUI or SwarmUI with ComfyUI backend on RunPod cloud platform, this is the ultimate tutorial that you will find to step by step install ComfyUI and SwarmUI on RunPod and use each one of them. RunPod is a great platform to scale your AI generation or if you are a GPU poor, rent the very best GPUs and leverage the AI in your profession. ComfyUI is the ultimate ecosystem right now for Image and Video generation models and with SwarmUI interface leveraging ComfyUI, you can become master for gen AI. So learn how to install ComfyUI on RunPod step by step and run it. Then learn how to install SwarmUI on RunPod step by step and learn how to use it. Then learn how to give installed ComfyUI backend to SwarmUI and leverage its features and ultimate performance and optimizations. Moreover, the installers I made installs Torch 2.7, CUDA 12.8, xFormers, Sage Attention, Flash Attention, Accelerate, Triton, DeepSpeed, ComfyUI manager and moΔ±re.
πComfyUI Installer Zip File Download ‡οΈ
βΆοΈ https://www.patreon.com/posts/Advanced-ComfyUI-1-Click-Installer-105023709
πSwarmUI Installer and Model Downloader Zip File Download ‡οΈ
βΆοΈ https://www.patreon.com/posts/SwarmUI-Installer-AI-Videos-Downloader-114517862
βΆοΈ Download & Upload Models Tutorial (wget) : https://youtu.be/X5WVZ0NMaTg
βΆοΈ CausVid LoRA V2 Tutorial : https://youtu.be/1rAwZv0hEcU
βΆοΈ CausVid Main Tutorial : https://youtu.be/fTzlQ0tjxj0
βΆοΈ SwarmUI Master Tutorial : https://youtu.be/HKX8_F1Er_w
π SECourses Official Discord 10500+ Members ‡οΈ
βΆοΈ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
π Stable Diffusion, FLUX, Generative AI Tutorials and Resources GitHub ‡οΈ
βΆοΈ https://github.com/FurkanGozukara/Stable-Diffusion
Tutorial Video : https://youtu.be/R02kPf9Y3_w
If you want to use ComfyUI or SwarmUI with ComfyUI backend on RunPod cloud platform, this is the ultimate tutorial that you will find to step by step install ComfyUI and SwarmUI on RunPod and use each one of them. RunPod is a great platform to scale your AI generation or if you are a GPU poor, rent the very best GPUs and leverage the AI in your profession. ComfyUI is the ultimate ecosystem right now for Image and Video generation models and with SwarmUI interface leveraging ComfyUI, you can become master for gen AI. So learn how to install ComfyUI on RunPod step by step and run it. Then learn how to install SwarmUI on RunPod step by step and learn how to use it. Then learn how to give installed ComfyUI backend to SwarmUI and leverage its features and ultimate performance and optimizations. Moreover, the installers I made installs Torch 2.7, CUDA 12.8, xFormers, Sage Attention, Flash Attention, Accelerate, Triton, DeepSpeed, ComfyUI manager and moΔ±re.
πComfyUI Installer Zip File Download ‡οΈ
βΆοΈ https://www.patreon.com/posts/Advanced-ComfyUI-1-Click-Installer-105023709
πSwarmUI Installer and Model Downloader Zip File Download ‡οΈ
βΆοΈ https://www.patreon.com/posts/SwarmUI-Installer-AI-Videos-Downloader-114517862
βΆοΈ Download & Upload Models Tutorial (wget) : https://youtu.be/X5WVZ0NMaTg
βΆοΈ CausVid LoRA V2 Tutorial : https://youtu.be/1rAwZv0hEcU
βΆοΈ CausVid Main Tutorial : https://youtu.be/fTzlQ0tjxj0
βΆοΈ SwarmUI Master Tutorial : https://youtu.be/HKX8_F1Er_w
π SECourses Official Discord 10500+ Members ‡οΈ
βΆοΈ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
π Stable Diffusion, FLUX, Generative AI Tutorials and Resources GitHub ‡οΈ
βΆοΈ https://github.com/FurkanGozukara/Stable-Diffusion
liked
a
Space
28 days ago
reacted to
merve's
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28 days ago
Post
2899
Qwen2.5-Omni is soooo good that people build multimodal reasoning models off of it π₯Ή
> KE-Team/Ke-Omni-R-3B is open-source audio reasoning model sota on average of benchmarks, based on Qwen/Qwen2.5-Omni-3B π£οΈ
> Haoz0206/Omni-R1 is a video reasoning model with pixel level grounding (see below) and it's super competitive β―οΈ based on Qwen/Qwen2.5-Omni-7B
> KE-Team/Ke-Omni-R-3B is open-source audio reasoning model sota on average of benchmarks, based on Qwen/Qwen2.5-Omni-3B π£οΈ
> Haoz0206/Omni-R1 is a video reasoning model with pixel level grounding (see below) and it's super competitive β―οΈ based on Qwen/Qwen2.5-Omni-7B
reacted to
Kseniase's
post with π₯π
28 days ago
Post
6156
12 Foundational AI Model Types
Letβs refresh some fundamentals today to stay fluent in the what we all work with. Here are some of the most popular model types that shape the vast world of AI (with examples in the brackets):
1. LLM - Large Language Model (GPT, LLaMA) -> Large Language Models: A Survey (2402.06196)
+ history of LLMs: https://www.turingpost.com/t/The%20History%20of%20LLMs
It's trained on massive text datasets to understand and generate human language. They are mostly build on Transformer architecture, predicting the next token. LLMs scale by increasing overall parameter count across all components (layers, attention heads, MLPs, etc.)
2. SLM - Small Language Model (TinyLLaMA, Phi models, SmolLM) A Survey of Small Language Models (2410.20011)
Lightweight LM optimized for efficiency, low memory use, fast inference, and edge use. SLMs work using the same principles as LLMs
3. VLM - Vision-Language Model (CLIP, Flamingo) -> An Introduction to Vision-Language Modeling (2405.17247)
Processes and understands both images and text. VLMs map images and text into a shared embedding space or generate captions/descriptions from both
4. MLLM - Multimodal Large Language Model (Gemini) -> A Survey on Multimodal Large Language Models (2306.13549)
A large-scale model that can understand and process multiple types of data (modalities) β usually text + other formats, like images, videos, audio, structured data, 3D or spatial inputs. MLLMs can be LLMs extended with modality adapters or trained jointly across vision, text, audio, etc.
5. LAM - Large Action Model (InstructDiffusion, RT-2) -> Large Action Models: From Inception to Implementation (2412.10047)
Understands and generates action sequences by predicting action tokens (discrete/continuous instructions) that guide agents. Trained on behavior datasets, LAMs generalize across tasks, environments, and modalities - video, sensor data, etc.
Read about LRM, MoE, SSM, RNN, CNN, SAM and LNN belowπ
Also, subscribe to the Turing Post: https://www.turingpost.com/subscribe
Letβs refresh some fundamentals today to stay fluent in the what we all work with. Here are some of the most popular model types that shape the vast world of AI (with examples in the brackets):
1. LLM - Large Language Model (GPT, LLaMA) -> Large Language Models: A Survey (2402.06196)
+ history of LLMs: https://www.turingpost.com/t/The%20History%20of%20LLMs
It's trained on massive text datasets to understand and generate human language. They are mostly build on Transformer architecture, predicting the next token. LLMs scale by increasing overall parameter count across all components (layers, attention heads, MLPs, etc.)
2. SLM - Small Language Model (TinyLLaMA, Phi models, SmolLM) A Survey of Small Language Models (2410.20011)
Lightweight LM optimized for efficiency, low memory use, fast inference, and edge use. SLMs work using the same principles as LLMs
3. VLM - Vision-Language Model (CLIP, Flamingo) -> An Introduction to Vision-Language Modeling (2405.17247)
Processes and understands both images and text. VLMs map images and text into a shared embedding space or generate captions/descriptions from both
4. MLLM - Multimodal Large Language Model (Gemini) -> A Survey on Multimodal Large Language Models (2306.13549)
A large-scale model that can understand and process multiple types of data (modalities) β usually text + other formats, like images, videos, audio, structured data, 3D or spatial inputs. MLLMs can be LLMs extended with modality adapters or trained jointly across vision, text, audio, etc.
5. LAM - Large Action Model (InstructDiffusion, RT-2) -> Large Action Models: From Inception to Implementation (2412.10047)
Understands and generates action sequences by predicting action tokens (discrete/continuous instructions) that guide agents. Trained on behavior datasets, LAMs generalize across tasks, environments, and modalities - video, sensor data, etc.
Read about LRM, MoE, SSM, RNN, CNN, SAM and LNN belowπ
Also, subscribe to the Turing Post: https://www.turingpost.com/subscribe
- 2 replies