JosephMinchala-skin-texture-zturbo-v45
JosephMinchala基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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NVFP4 quantization of JonathanColetti/Qwen3.8-27B-Uncensored, produced with NVIDIA TensorRT Model Optimizer 0.43.0 for Blackwell-class inference under vLLM. **~65 GB bf16 → 19.2 GiB.** The multi-token-prediction head and the vision tower are both retained. Qwen3.8-27B is a hybrid stack — 64 layers of `3× (Gated DeltaNet → FFN) + 1× (Gated Attention → FFN)`. The DeltaNet decay and beta projections (`in_proj_a` / `in_proj_b`) are low-rank and precision-sensitive, so they are left at bf16 along with the causal `conv1d`.
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View details ↗This model was converted to GGUF format from `meta-llama/Meta-Llama-3.1-8B-Instruct` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
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View details ↗mformer-authority
joshnguyen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗mformer-care
joshnguyen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗mformer-fairness
joshnguyen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗mformer-loyalty
joshnguyen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗mformer-sanctity
joshnguyen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Muse-Spark-Open-816B-A42B-MLX-2bit-mixed
joshuaswarren基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗milliontrees-detr
joshvm基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗mt5-small-spanish-summarization
josmunpen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Bifrost-27B-GGUF
Joumdane基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗DeepCoder-14B-Preview-GGUF
Joumdane基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗vlm-3r-llava-qwen2-lora
Journey9ni基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗JoyFox-Qwen3.6-35B-A3B-RP-Aggressive is designed for sustained character voice, direct instruction following, coherent scene continuation, low role-break frequency, and long-context creative dialogue. It combines roleplay supervised fine-tuning, preference optimization, explicit response-length control, and a final activation-space refusal-direction intervention. The model retains the original Qwen3.6 multimodal architecture, 262K native context, Mixture-of-Experts routing, and native Multi-Token Prediction head. The Aggressive variant applies the stronger form of the refusal-direction intervention. It is intended to answer directly instead of falling into repetitive policy-style refusals, prematurely ending a scene, or breaking character. “Aggressive” describes the strength of the behavioral intervention, not the model's personality or default writing tone.
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View details ↗JoyFox-Reverie-27B
joyfox基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗LTX-2.3-Transition-LORA
joyfoxThis LoRA is trained on top of **Lightricks/LTX-2.3** and is built with a custom training paradigm tailored for high-consistency video generation. It was originally optimized for **first-frame / last-frame guided transition videos**, but the same training strategy also gives it strong generalization in: - **First-to-last frame video generation** - **Text-to-video** - **Image-to-video** - **Stylized transformation and scene transition generation**
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View details ↗LTX2.3-ICEdit-Insight
joyfox**LTX2.3-ICEdit-Insight** is a task-aware video restoration and editing model family developed by **JoyFox Lab**, built on top of the **LTX-2.3 DiT-based audio-video foundation model**. - **Video Restoration**: degradation recovery, compression cleanup, blur and noise reduction, and damaged detail restoration. - **Video HD Enhancement**: super-resolution, detail reconstruction, texture sharpening, and perceptual quality improvement. - **Watermark Removal**: logo cleanup, semi-transparent overlay removal, and occlusion-aware background reconstruction. - **Subtitle Removal**: hard subtitle removal, caption cleanup, text overlay removal, and temporally stable inpainting. Unlike conventional frame-level enhancement pipelines, this model family operates as a **generative video restoration system** in latent video space. It is designed to preserve global structure, camera motion, object identity, and temporal consistency while reconstructing missing or degraded visual content.
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗This is a model for High-definition magnification of the picture, trained on , and it is mainly used for losslessly enlarging images to approximately 2K size.For use in . ComfyUI Workflow This LoRA works with a modified version of Comfy's Qwen/Qwen-Image-Edit-2509 workflow . The main modification is adding a Qwen/Qwen-Image-Edit-2509 LoRA node connected to the base model. See the Downloads section above for the modified workflow. There is no fixed trigger word. The specific removal prompt needs to be tested more
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen-Image-Edit-MeiTu
joyfox基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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