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AI Models 84759

• nsfwMarrier↗

  asezualdemifluid

• SmolLM3-3B-GGUF↗

  Bastion-AI

• Qwen2.5-VL-7B-Instruct-GGUF↗

  benxh

• GLM-5.2-EXL3-TR3v4-3.5bpw-MTP78↗

  brandonmusic

  There is **no universal current default launcher** across the historical profiles retained in this card. For a new deployment, do not infer a default from an older section: The portable r17 package becomes the recommended downloadable path only after it repeats the end-to-end graph, task, 260K retrieval, and numerical gates on the corrected dual-ABI build. An immutable five-fresh-boot acceptance panel plus a factorial G64-Q-only follow-up compared the r17 FP8 MLA reader paths. Lower KLD is better.

• flux1-gguf↗

  calcuis

  get the comfy pack*: - decompress the 7z bundle file: Extract All... (it includes everything you need to run a model) - download flux1-dev-Q4_0.gguf (6.32GB); pull it to ./ComfyUI/models/unet - download clip_l.safetensors (246MB); pull it to ./ComfyUI/models/clip - download t5xxl_fp8_e4m3fn.safetensors (4.89GB); pull it to ./ComfyUI/models/clip - download ae.safetensors (319MB); pull it to ./ComfyUI/models/vae - run the .bat file in the main directory (it will activate the py backend as well as the js frontend) - drag gguf-workflow.json to the activated browser

• twitter-roberta-base-hate-latest↗

  cardiffnlp

  This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2022-154m for binary hate-speech classification. A combination of 13 different hate-speech datasets in the English language were used to fine-tune the model. More details in the reference paper.

• distilroberta-base-climate-detector↗

  climatebert

• muscriptor-large↗

  cocktailpeanut

  **MuScriptor** is an open-weight model for **general-purpose, multi-instrument automatic music transcription (AMT)**: it converts a music recording (any genre, multiple simultaneous instruments) into a stream of notes played. This repository hosts the **large** variant (≈1.3B parameters) — the **flagship, best-quality checkpoint**. For a smaller footprint use `muscriptor-medium` (≈300M, good trade-off) or `muscriptor-small` (≈100M, fastest). `load_model` accepts a size keyword (`"small"`/`"medium"`/`"large"`), a local `.safetensors` path, or an `hf://` / `https://` URL. Weights loaded by size keyword (or any `hf://` URL) are cached in the standard Hugging Face cache (`~/.cache/huggingface/hub`, configurable via `HF_HOME`); weights fetched from a plain `http(s)://` URL are cached under `~/.cache/muscriptor/`. Input audio can be WAV or any format `libsndfile` reads (mp3, flac, ogg, m4a, …); it is resampled to 16 kHz mono internally.

• Qwen3-0.6B-accuracy-recovery-lora↗

  codelion

• CommonCanvas-XL-C↗

  common-canvas