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QwenLM/Qwen-Agent: Agent framework and applications built upon Qwen=2.0, featuring Function Calling, Code Interpreter, RAG, and Chrome extension.
QwenLM/Qwen-Agent: Agent framework and applications built upon Qwen=2.0, featuring Function Calling, Code Interpreter, RAG, and Chrome extension.
Agent framework and applications built upon Qwen=2.0, featuring Function Calling, Code Interpreter, RAG, and Chrome extension. - QwenLM/Qwen-Agent
AI LLM#Source Code: GitHub#Type: Open-Source
·github.com·
QwenLM/Qwen-Agent: Agent framework and applications built upon Qwen=2.0, featuring Function Calling, Code Interpreter, RAG, and Chrome extension.
MustardChef/WSABuilds: Run Windows Subsystem For Android on your Windows 10 and Windows 11 PC using prebuilt binaries with Google Play Store (MindTheGapps) and/or Magisk or KernelSU (root solutions) built in.
MustardChef/WSABuilds: Run Windows Subsystem For Android on your Windows 10 and Windows 11 PC using prebuilt binaries with Google Play Store (MindTheGapps) and/or Magisk or KernelSU (root solutions) built in.
Run Windows Subsystem For Android on your Windows 10 and Windows 11 PC using prebuilt binaries with Google Play Store (MindTheGapps) and/or Magisk or KernelSU (root solutions) built in. - MustardC...
Android emulator#Source Code: GitHub#Type: Open-Source
·github.com·
MustardChef/WSABuilds: Run Windows Subsystem For Android on your Windows 10 and Windows 11 PC using prebuilt binaries with Google Play Store (MindTheGapps) and/or Magisk or KernelSU (root solutions) built in.
zignd/HTML-CSS-Class-Completion: Visual Studio Code extension that provides CSS class name completion for the HTML class attribute based on the CSS files in your workspace
zignd/HTML-CSS-Class-Completion: Visual Studio Code extension that provides CSS class name completion for the HTML class attribute based on the CSS files in your workspace
:chocolate_bar: Visual Studio Code extension that provides CSS class name completion for the HTML class attribute based on the CSS files in your workspace - GitHub - zignd/HTML-CSS-Class-Completio...
VSCode extension#Source Code: GitHub#Type: Open-Source
·github.com·
zignd/HTML-CSS-Class-Completion: Visual Studio Code extension that provides CSS class name completion for the HTML class attribute based on the CSS files in your workspace
Stability-AI/StableSwarmUI: StableSwarmUI, A Modular Stable Diffusion Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility.
Stability-AI/StableSwarmUI: StableSwarmUI, A Modular Stable Diffusion Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility.
StableSwarmUI, A Modular Stable Diffusion Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility. - Stability-AI/StableSwarmUI
AI LLM#Source Code: GitHub#Type: Open-Source
·github.com·
Stability-AI/StableSwarmUI: StableSwarmUI, A Modular Stable Diffusion Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility.
BlinkDL/RWKV-LM: RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
BlinkDL/RWKV-LM: RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast in...
AI LLM#Source Code: GitHub#Software: LLM#Software: AI#Type: Open-Source
·github.com·
BlinkDL/RWKV-LM: RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.