Qwen3.8-27B-AWQ-INT4
abihsoro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 ↗DISCOVER & COMPARE
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whisper-telephony-amd
AbijahKaj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 ↗sentiment-binary-dicoding
abilfad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 ↗whisper-turbo-ksc2
abilmansplus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 ↗gpt-2-tamil
abinayam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 ↗10Eros-Max-GGUF
Abiray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 ↗**A highly optimized, consumer-hardware-friendly GGUF quantization of TenStrip's 10Eros-Max Hybrid Beta 5.** Choose the quant that best matches your GPU. *(Note: You will also need VRAM overhead for the Qwen3-VL Text Encoder, Video VAE, and Audio VAE).* These GGUFs were engineered for maximum compatibility. To bypass architecture-checking limitations in current loaders, **the architecture header has been spoofed as `"wan"`**.
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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 ↗High-performance **GGUF quantizations** of TenStrip's 10Eros-Max Turbo Hybrid Beta 5, a fine-tuned, step-distilled video-and-audio model built on the **MiniMax H3** DiT architecture. These quantizations compress the original **40.2 GB FP16/BF16** weights down to **8.9 GB – 16.7 GB**, enabling fast local inference on consumer and prosumer GPUs inside ComfyUI without degrading motion dynamics or facial detail. All quants were compiled with custom **1D tensor shielding** and **K-quant divisibility folding** using patched `llama.cpp` and `ComfyUI-GGUF`.
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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 ↗Anima-base-v1.0-GGUF
AbirayThis repository contains GGUF weights for Anima-base-v1.0, a 2B parameter diffusion model based on the **NVIDIA Cosmos** architecture. These weights have been quantized using a specialized pipeline to ensure maximum compatibility and image quality on consumer hardware. To ensure the highest possible quality and avoid the "BF16 noise bug" common in diffusion quantization, the following steps were taken: 1. **FP32 Casting:** The original BF16 `safetensors` were cast to `FP32` before conversion. 2. **Architecture Patching:** Used a patched version of `llama.cpp` (based on build `b3962`) with the `city96` diffusion patch to support the `cosmos` architecture. 3. **Precision Preservation:** Sensitive layers (normalizations and biases) were kept in `F32` to prevent color banding and generation artifacts.
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View details ↗Anima-turbo-v1.0-GGUF
Abiray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 ↗Artemis-31B-v1.2-GGUF
AbirayArtemis-31B-v1.2 is a fine-tuned, unaligned creative writing and roleplay model built on Google's **Gemma 4 31B** base architecture. It is specifically calibrated for literary depth, psychological nuance, long-horizon scene continuity, and multi-turn roleplay. Artemis-31B uses the **Gemma 4 Chat Template** and natively supports both **Thinking (Reasoning Scratchpad)** and **Direct Storytelling** operational modes. Trigger the reasoning planner by embedding ` ` into the prompt. The model will plan character motivations, spatial distance, and scene tone in a scratchpad before generating the visible narrative.
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View details ↗ComfyUI-Qwen3-VL-GGUF
AbirayThis repository provides **two distinct formats** depending on your runtime: 1. **🔥 NEW: Unified Single-File Hybrid GGUFs (`*_vision_q8_0.gguf`)** — Combines the K-quantized LLM backbone (`Q4_K_M` / `Q5_K_M`) and the `Q8_0` Vision Tower + DeepStack Mergers + 5D `Conv3d` shape metadata (`comfy.gguf.orig_shape`) inside a **single file**. 2. **Split LLM + Standalone `mmproj` GGUFs** — Standard two-file format for **llama.cpp**, **llama-server**, **Ollama**, and split VLM loaders. *Contains both the Language Backbone (`blk.*`) and Vision Tower (`model.visual.*`) in a single GGUF file.* 1. Download either `qwen3vl_8b_q4_k_m_vision_q8_0.gguf` or `qwen3vl_8b_q5_k_m_vision_q8_0.gguf` and place it into:
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View details ↗This repository provides a **standalone, weight-baked abliterated (uncensored) GGUF build** of `ISTA-DASLab/DeepSeek-V4.1-Flash-1017-GSQ-RCO-GGUF` (`IQ2_XXS`, 2.00 bpw) using the rank-1 EN+RU refusal-direction abliteration from `AtomicChat/DeepSeek-V4.1-Flash-1017-Uncensored-GGUF`. - **Zero LoRA Required at Runtime:** All 86 abliterated residual-writing tensors are baked directly into the 4 GGUF backbone shards. No `--lora` adapter flags are needed. - **Same Size as Original (`138.58 GB` vs. `138.24 GB`):** Adds only `+0.34 GB` (`+0.25%`) across the entire 4-shard 763B model. - **100% GSQ-RCO Intelligence Preserved:** All **28 1-bit `IQ1_M` GSQ-calibrated routed-expert layers** and both **`blk.{1,14}.engram_wkv.weight` (`Q5_K`)** projections from ISTA-DASLab are preserved 100% untouched, while all **80 dense residual writers** (`blk.{0..39}.attn_output_b.weight` in `Q6_K` and `blk.{0..39}.ffn_down_shexp.weight` in `Q8_0`/`Q5_K`) plus the **6 exact-type 2-bit routed-expert layers** (`blk.7, 8, 10, 18` in `IQ2_XXS` and `blk.33, 39` in `IQ2_XS`) carry the full refusal-direction removal. > **Important:** Like the upstream ISTA-DASLab release, this 4-shard backbone pairs with the shared **`DeepSeek-V4.1-Flash-Engram-IQ4_NL.gguf`** (`110.60 GB`) lookup file from `ISTA-DASLab/DeepSeek-V4.1-Flash-1017-GSQ-RCO-GGUF`. Place all 4 shards and the Engram file in the same directory.
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View details ↗Fara1.5-27B-GGUF
Abiray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 ↗FastH3-Omni-GGUF
AbirayHigh-precision **GGUF quantizations** of **FastVideo/FastH3-Omni-Comfy** (`fasth3_omniref_8step_pruned_bf16.safetensors`), the **8-step consistency-distilled Omni-Reference (`Ref2VA`)** model built on **MiniMax-H3** by FastVideo (Hao AI Lab) in collaboration with Nuva Lab and Reactor. Unlike standard naive quantizations that crush timestep modulation tables and output heads into low-bit blocks, **this GGUF suite uses hybrid precision shielding** to keep critical audio/video decoding heads, 32-head PDD (Progressive Distillation) offsets, and AdaLN interpolation tables in **lossless `FP32`**, while compressing the 50-block DiT + Video Sparse Attention (`VSA`) backbone for consumer RTX GPUs. All files are converted from the **44.24 GB Pruned BF16** checkpoint (`FastVideo/FastH3-Omni-Comfy`) compatibility with `city96/ComfyUI-GGUF`.
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View details ↗Fibo-2.0-edit-turbo-GGUF
Abiray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 ↗GGUF quantizations of Black Forest Labs' FLUX 3 Image Klein (16-step distilled checkpoint) for use with ComfyUI-GGUF. A pre-configured Text-to-Image (T2I) workflow is included in this repository: * **Download Workflow:** image_flux3_klein_distilled_t2i_GGUF.json A pre-configured Image-edit (I2I) workflow is included in this repository: * **Download Workflow:** image_flux3_klein_distilled_image_edit_GGUF.json
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