全站搜索

AI 模型 84759

• prompt-injection-guard-small↗

  Horizon-Labs

• Hyper-SD↗

  字节跳动

  Official Repository of the paper: *Hyper-SD*. * Aug.26, 2024. 💥💥💥 Our 8-steps and 16-steps **FLUX.1-dev-related LoRAs** are available now! We recommend LoRA scales around 0.125 that is adaptive with training and guidance scale could be kept on 3.5. Lower step LoRAs would be coming soon. 💥💥💥 * Aug.19, 2024. SD3-related CFG LoRAs are available now! We recommend setting guidance scale to 3.0/5.0/7.0 at 4/8/16-steps. Don't forget to fuse lora with a relatively small scale (e.g. 0.125 that is adaptive with training) before inference with diffusers. Note that 8-steps and 16-steps LoRA can also inference on a little bit smaller steps like 6-steps and 12-steps, respectively. Hope to hear your feedback, FLUX-related models will be coming next week. * May.13, 2024. The 12-Steps CFG-Preserved Hyper-SDXL-12steps-CFG-LoRA and Hyper-SD15-12steps-CFG-LoRA is also available now(support 5~8 guidance scales), this could be more practical with better trade-off between performance and speed. Enjoy! * Apr.30, 2024. Our 8-Steps CFG-Preserved Hyper-SDXL-8steps-CFG-LoRA and Hyper-SD15-8steps-CFG-LoRA is available now(support 5~8 guidance scales), we strongly recommend making the 8-step CFGLora a standard configuration for all SDXL and SD15 models!!! * Apr.28, 2024. ComfyUI workflows on 1-Step Unified LoRA 🥰 with TCDScheduler to inference on different steps are released! Remember to install ⭕️ ComfyUI-TCD in your `ComfyUI/custom_nodes` folder!!! You're encouraged to adjust the eta parameter to get better results 🌟! * Apr.26, 2024. Thanks to @Pete for contributing to our scribble demo with larger canvas right now 👏. * Apr.24, 2024. The ComfyUI workflow and checkpoint on 1-Step SDXL UNet ✨ is also available! Don't forget ⭕️ to install the custom scheduler in your `ComfyUI/custom_nodes` folder!!! * Apr.23, 2024. ComfyUI workflows on N-Steps LoRAs are released! Worth a try for creators 💥! * Apr.23, 2024. Our technical report 📚 is uploaded to arXiv! Many implementation details are provided and we welcome more discussions👏. * Apr.21, 2024. Hyper-SD ⚡️ is highly compatible and work well with different base models and controlnets. To clarify, we also append the usage example of controlnet here. * Apr.20, 2024. Our checkpoints and two demos 🤗 (i.e. SD15-Scribble and SDXL-T2I) are publicly available on HuggingFace Repo. Hyper-SD Scribble demo host on 🤗 scribble

• Jais-3-MoVA-36B-A4B-GGUF↗

  IFM

• gemma-4-E4B-it-SDFT_Heretic_RP-GGUF↗

  Ilya626

• Ling-3.0-tiny-GGUF↗

  inclusionAI

  🤗 Hugging Face    |   🤖 ModelScope    |   🐙 OpenRouter    Ling-3.0-tiny is a lightweight hybrid reasoning MoE model with **7.9B** total parameters and only **1.3B** activated parameters per token. It is designed to deliver strong reasoning and agentic capabilities at low inference cost, making advanced model capabilities more accessible for local and resource-constrained deployment. Find more details in the original model card: https://huggingface.co/inclusionAI/Ling-3.0-tiny

• UniReason-Med↗

  IQuestLab

• gemma-4-12B-it-qat-assistant-MTP-Q8_0-GGUF↗

  Janvitos

• qwen3.5-9b-jspace-abliterated-GGUF↗

  jwest33

• svara-tts-v1↗

  kenpath

  **svara-TTS** is a developer-first multilingual TTS model for **19 languages** (18 Indic + Indian English). Built on an Orpheus-style discrete audio token approach, it targets **clarity, expressiveness, and low-latency** on commodity GPUs/CPUs. It supports light-weight **emotion/style control** (e.g., ` `, ` `, ` `, ` `) and simple **speaker identities** (`Language (Gender)`), with **zero-shot** adaptation paths. - **Languages (19):** Hindi, Bengali, Marathi, Telugu, Kannada, Bhojpuri, Magahi, Chhattisgarhi, Maithili, Assamese, Bodo, Dogri, Gujarati, Malayalam, Punjabi, Tamil, Nepali, Sanskrit, Indian English. - **Expressivity:** End-of-utterance style tags; natural prosody; code-switch aware. - **Latency & Deployment:** Works well with **GGUF** exports; suitable for edge/CPU scenarios. - **Adaptability:** **LoRA-friendly** for quick speaker/domain specialization. Try it live on the **Demo Space**, or on **Colab** Deployment scripts and **inference repo** will be available soon. Watch our Github for updates

• sft_gemma2_2b_layerdrop_p005↗

  KexuanShi