**ROCmFPX quantized GGUF (7 tiers + vision mmproj)** of huihui-ai/Huihui-Ornith-1.5-35B-A3B-abliterated — abliterated BF16 weights, locally quantized. > **Base model license**: `ornith-ai/Ornith-1.5-35B-A3B` is MIT-licensed; its copyright notice and license text are retained. The packaging of this quantization is Apache-2.0. This repository uses strix.cpp, a llama.cpp fork **specifically tuned for the AMD Strix Halo `gfx1151` (Ryzen AI MAX+ 395) UMA architecture and ROCm/HIP backend**, with native support for the ROCmFPX quantization format.

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Ornith-1.5-35B-A3B-ROCmFPX

ArtomYuan

**ROCmFPX quantized GGUF (7 tiers + vision mmproj)** of ornith-ai/Ornith-1.5-35B-A3B — the official base model, locally requantized. > **Base model license**: `ornith-ai/Ornith-1.5-35B-A3B` is MIT-licensed; its copyright notice and license text are retained. The packaging of this quantization is Apache-2.0. This repository uses strix.cpp, a llama.cpp fork **specifically tuned for the AMD Strix Halo `gfx1151` (Ryzen AI MAX+ 395) UMA architecture and ROCm/HIP backend**, with native support for the ROCmFPX quantization format.

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Qwen3.8-27B-abliterated-ROCmFPX

ArtomYuan

**ROCmFPX quantized GGUF (7 tiers + vision mmproj)** of huihui-ai/Huihui-Qwen3.8-27B-abliterated — abliterated BF16 weights, locally requantized. This repository uses strix.cpp, a llama.cpp fork **specifically tuned for the AMD Strix Halo `gfx1151` (Ryzen AI MAX+ 395) UMA architecture and ROCm/HIP backend**, with native support for the ROCmFPX quantization format. Requires strix.cpp (this fork supports ROCmFPX; **upstream llama.cpp cannot load these files** — format note at the end).

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Qwen3.8-27B-Coder390-EfficientThink-abliterated-ROCmFPX

ArtomYuan

**ROCmFPX quantized GGUF (7 tiers + vision mmproj)** of huihui-ai/Huihui-Qwen3.8-27B-Coder390-EfficientThink-abliterated — abliterated BF16 weights of the Coder390-EfficientThink finetune, locally requantized. This repository uses strix.cpp, a llama.cpp fork **specifically tuned for the AMD Strix Halo `gfx1151` (Ryzen AI MAX+ 395) UMA architecture and ROCm/HIP backend**, with native support for the ROCmFPX quantization format. Requires strix.cpp (this fork supports ROCmFPX; **upstream llama.cpp cannot load these files** — format note at the end).

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Qwen3.8-27B-ROCmFPX

ArtomYuan

**ROCmFPX quantized GGUF (7 tiers + vision mmproj)** of Qwen/Qwen3.8-27B — official BF16 weights, locally requantized. This repository uses strix.cpp, a llama.cpp fork **specifically tuned for the AMD Strix Halo `gfx1151` (Ryzen AI MAX+ 395) UMA architecture and ROCm/HIP backend**, with native support for the ROCmFPX quantization format. Requires strix.cpp (this fork supports ROCmFPX; **upstream llama.cpp cannot load these files** — format note at the end).

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Qwen3.8-Flash-Next-ROCmFPX

ArtomYuan

**ROCmFPX quantized GGUF of Qwen3.8-Flash-Next (7 tiers + vision mmproj)** — locally requantized from the official Qwen/Qwen3.8-Flash-Next. > **License**: this quantization follows the base model's Qwen Community License 1.0. It is **not** Apache-2.0. Requires strix.cpp (this fork supports ROCmFPX; **upstream llama.cpp cannot load this batch** — see the Format Note at the end).

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SraVaani-0.5-live

ARTPARK-IISc

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。

语音识别

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SraVaani-1.0

ARTPARK-IISc

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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Vaani-LID_v0

ARTPARK-IISc

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。

基础资料已收录 · 缺失资料后续补充

向量与相似度

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whisper-large-v3-vaani-hindi

ARTPARK-IISc

This is a fine-tuned version of OpenAI's Whisper-Large-V3, trained on approximately 718 hours of transcribed Hindi speech from multiple datasets. The models has finetuned using folllowing dataset Vaani ,Gramvaani IndicVoices, Fleurs,IndicTTS and Commonvoice The performance of the model was evaluated using multiple datasets, and the evaluation results are provided below.

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L-MChat-7b

Artples

L-MChat-7b is a merge of the following models: * Nexusflow/Starling-LM-7B-beta * FuseAI/FuseChat-7B-VaRM

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L-MChat-Small

Artples

This was a test of mine how small merges perform, because there are a lot of 7b merges and higher but not a lot of 2b merges. The following models were included in the merge: * rhysjones/phi-2-orange-v2 * Weyaxi/Einstein-v4-phi2 Use it with the ChatML format, you can also use the Inference-API for this Model. Detailed results can be found here

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