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AI モデル 85003

• Qwen3.8-27B-Heretic-GSQ-RCO-GGUF↗

  0bserverx

  **Non-uniform GGUF quantizations** of **RVN Qwen3.8-27B-Heretic-Abliterated-Uncensored** (refusals 0-1/100, KL ~ 0.0085 vs base). Instead of one uniform quantization type for all tensors, **each of the 851 tensors carries its own type**, following the per-tensor **RCO allocation** published by IST-DASLab for their GSQ-RCO release of Qwen3.8-27B, quantized locally with **llama.cpp** and the **official importance matrix** `imatrix-qwen3.8-27b.gguf`. Files are standard GGUF and run unmodified in llama.cpp / Ollama / LM Studio. This family was made at the request of community member **Heidagger44** in discussion #11: > Regarding IQ3_S there is new method: GSQ-RCO, if it's possible to combine your abliteration method with this quantization, we would have a true refusal free Qwen3.8-27B running fully on 16GB cards.

• unifiedqa-v2-t5-base-1251000↗

  allenai

• flux-koda↗

  alvdansen

• ocr-captcha-v2↗

  anuashok

  This model is a fine-tuned version of microsoft/trocr-base-printed on your custom dataset. captchas like processor = TrOCRProcessor.from_pretrained("anuashok/ocr-captcha-v2") model = VisionEncoderDecoderModel.from_pretrained("anuashok/ocr-captcha-v2") generated_ids = model.generate(pixel_values) generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] print(generated_text)

• hkust-nlp_dsv2-lite-coder_codeio_pp-GGUF↗

  bartowski

• Meta-Llama-3-70B-Instruct-GGUF↗

  bartowski

  If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (Meta-Llama-3-70B-Instruct-Q8_0) or download them all in place (./) The first thing to figure out is how big a model you can run. To do this, you'll need to figure out how much RAM and/or VRAM you have.

• PubMedBERT-base-uncased-sts-combined↗

  bcwarner

• Qwen2.5-3B-Instruct-abliterated.Q4_K_M.gguf↗

  Bluerosesbutterfly

• flint-oQ3.5e-fp16↗

  chimpanzeetaxidriver

• flux2-klein-GGUF↗

  ChrisColeTech

  > **What this repo is:** a requantized, split-layout build of the upstream model — weights only, not a retrain. The recommended settings below are the values these weights are actually run with day to day, not copied from the upstream card. **prompt:** `a red apple on a rustic wooden table beside a window, soft daylight, fine skin texture and wood grain, studio photograph, sharp focus` — 1024×1024, 4 steps, guidance 1.0, seed 12345 **prompt:** `portrait of an older fisherman with a weathered face, natural window light, shallow depth of field, photorealistic` — 1024×1024, 4 steps, guidance 1.0, seed 99 **prompt:** `a rain-slicked Tokyo street at night, neon signs reflecting in puddles, cinematic, 35mm photograph` — 1024×1024, 4 steps, guidance 1.0, seed 1234