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AI モデル 84759

• mobilenetv3_rw.rmsp_in1k↗

  timm

• Lumina-Image-2.0↗

  unsloth

• NVIDIA-Nemotron-3-Nano-4B-BF16-i1-GGUF↗

  VAREQON

• 5GHagCGfeLubZsVRVWTjys216dgszre1M4etHJ57tSYnKpsG_vgg↗

  ven1228

• all-MiniLM-L6-v2↗

  Xenova

  https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2 with ONNX weights to be compatible with Transformers.js. Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

• MiMo-V2.5-Pro-FP4-DFlash↗

  XiaomiMiMo

• Qwen3-4B-RPG-Roleplay-V2↗

  Zlatiik

• Qwen2.5-Coder-0.5B-Instruct-Gensyn-Swarm-tall_tame_panther↗

  0xgr3y

  Our pick an **experimental (advanced) mode** at this model a continuously trained `Qwen2.5-Coder-0.5B-Instruct` fine-tuned using **Gensyn RL-Swarm** framework with **GRPO (Group Relative Policy Optimization)** and supported format **GGUF (llama.cpp)** for enhanced code generation capabilities. **Note: Current training focuses on programming challenges with adaptive weighted sampling**. **Total Dataset Size:** Streaming datasets with infinite iteration **Training Samples per Round:** 2 **Evaluation:** Real-time via Swarm Coordination with Ollama-based evaluator else Judge > "When the solvers perform well, the proposer automatically increases the difficulty to keep challenging solvers to get better over time." - CodeZero-blog

• GLM-4.7-Flash-Name-NSFW-GGUF↗

  2048lr

• AnimeGen-T2V↗

  aidealab