modelId stringlengths 9 107 | author stringlengths 3 37 | last_modified timestamp[us, tz=UTC]date 2021-03-22 21:11:33 2026-05-04 17:37:22 | downloads int64 100 72.3M | likes int64 1 4.99k | library_name stringclasses 132
values | tags listlengths 2 2.16k | pipeline_tag stringclasses 52
values | createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2026-05-03 03:15:09 | card stringlengths 1.51k 391k | entities listlengths 0 18 |
|---|---|---|---|---|---|---|---|---|---|---|
mradermacher/Noir-Ultra-GGUF | mradermacher | 2026-04-22T09:30:40Z | 304 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen2",
"reasoning",
"science",
"logic",
"trl",
"sft",
"en",
"ru",
"zh",
"base_model:muverqqw/Noir-Ultra",
"base_model:quantized:muverqqw/Noir-Ultra",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conv... | null | 2026-03-05T01:26:51Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [
{
"start": 361,
"end": 371,
"text": "Noir-Ultra",
"label": "benchmark name",
"score": 0.6263689994812012
},
{
"start": 508,
"end": 523,
"text": "Noir-Ultra-GGUF",
"label": "benchmark name",
"score": 0.7447598576545715
},
{
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"end": 1234,
"text... |
tiantiaf/whisper-large-v3-speech-flow | tiantiaf | 2025-08-10T21:37:49Z | 669 | 2 | null | [
"safetensors",
"model_hub_mixin",
"pytorch_model_hub_mixin",
"audio-classification",
"en",
"arxiv:2505.14648",
"base_model:openai/whisper-large-v3",
"base_model:finetune:openai/whisper-large-v3",
"license:openrail",
"region:us"
] | audio-classification | 2025-05-22T04:37:39Z | # Whisper Large v3 for Speech Flow (Fluency) Classification
# Model Description
This model includes the implementation of speech fluency classification described in Vox-Profile: A Speech Foundation Model Benchmark for Characterizing Diverse Speaker and Speech Traits (https://arxiv.org/pdf/2505.14648)
The model first ... | [
{
"start": 166,
"end": 177,
"text": "Vox-Profile",
"label": "benchmark name",
"score": 0.8645176291465759
}
] |
nota-ai/ERGO-7B | nota-ai | 2026-02-25T04:50:50Z | 118 | 15 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"conversational",
"arxiv:2509.21991",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-10-02T01:08:09Z | # ERGO: Efficient High-Resolution Visual Understanding for Vision-Language Models
<p align="center">
<a href="https://arxiv.org/abs/2509.21991">
<img src="https://img.shields.io/badge/arXiv-paper-red"></a>
<a href="https://github.com/nota-github/ERGO.git">
<img src="https://img.shields.io/badge/github-code... | [
{
"start": 2,
"end": 6,
"text": "ERGO",
"label": "benchmark name",
"score": 0.909360408782959
},
{
"start": 255,
"end": 259,
"text": "ERGO",
"label": "benchmark name",
"score": 0.8405291438102722
},
{
"start": 579,
"end": 583,
"text": "ERGO",
"label": ... |
madebyollin/sdxl-vae-fp16-fix | madebyollin | 2024-02-03T17:10:22Z | 258,460 | 612 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"license:mit",
"region:us"
] | null | 2023-07-11T04:03:50Z | # SDXL-VAE-FP16-Fix
SDXL-VAE-FP16-Fix is the [SDXL VAE](https://huggingface.co/stabilityai/sdxl-vae)*, but modified to run in fp16 precision without generating NaNs.
| VAE | Decoding in `float32` / `bfloat16` precision | Decoding in `float16` precision |
| --------------------- | -------------------... | [] |
PerceptronAI/Isaac-0.2-2B-Preview | PerceptronAI | 2025-12-21T01:20:35Z | 78,977 | 10 | null | [
"safetensors",
"isaac",
"image-text-to-text",
"conversational",
"custom_code",
"en",
"license:cc-by-nc-4.0",
"region:us"
] | image-text-to-text | 2025-12-10T05:26:37Z | # Isaac-0.2-2B by Perceptron
Introducing the 2B parameter variant of Isaac-0.2, the hybrid-reasoning vision-language model.
This release brings major upgrades — optional reasoning via thinking traces, perceptive tool calling (including our new Focus system), stronger grounding, better OCR, better desktop use, and imp... | [] |
prithivMLmods/Flux-Realism-FineDetailed | prithivMLmods | 2024-11-13T08:51:30Z | 213 | 25 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"Realism",
"Fine-Detailed",
"Flux.1-dev",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2024-11-09T14:29:09Z | ## Flux-Realism-FineDetailed - B+ 20
<Gallery />
- Hosted Here🧨: https://huggingface.co/spaces/prithivMLmods/FLUX-LoRA-DLC
**The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.**
## Model description
**prithivMLmods/Flux-Realism-Fin... | [] |
mradermacher/Magidonia-24B-v4.3-heretic-v2-GGUF | mradermacher | 2025-12-21T18:21:41Z | 552 | 2 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:coder3101/Magidonia-24B-v4.3-heretic-v2",
"base_model:quantized:coder3101/Magidonia-24B-v4.3-heretic-v2",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-21T12:45:38Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [
{
"start": 528,
"end": 562,
"text": "Magidonia-24B-v4.3-heretic-v2-GGUF",
"label": "benchmark name",
"score": 0.6856114268302917
}
] |
5CD-AI/Vintern-1B-v3_5 | 5CD-AI | 2025-12-10T16:20:55Z | 12,404 | 115 | transformers | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"image-text-to-text",
"conversational",
"custom_code",
"vi",
"en",
"zh",
"arxiv:2408.12480",
"base_model:OpenGVLab/InternVL2_5-1B",
"base_model:finetune:OpenGVLab/InternVL2_5-1B",
"license:mit",
"region:us"
] | image-text-to-text | 2025-01-11T18:12:55Z | <div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6336b5c831efcb5647f00170/-G297bBqMzYvTbD6_Bkd9.png" width="500"/>
</div>
# Vintern-1B-v3.5 ❄️
We introduce **Vintern-1B-v3.5**, the latest version in the Vintern series, offering significant improvements over v2 across all evaluat... | [
{
"start": 164,
"end": 179,
"text": "Vintern-1B-v3.5",
"label": "benchmark name",
"score": 0.6641704440116882
},
{
"start": 199,
"end": 214,
"text": "Vintern-1B-v3.5",
"label": "benchmark name",
"score": 0.7743671536445618
},
{
"start": 1050,
"end": 1065,
... |
suno/bark-small | suno | 2023-11-10T10:11:12Z | 27,753 | 256 | transformers | [
"transformers",
"pytorch",
"bark",
"text-to-audio",
"audio",
"text-to-speech",
"en",
"de",
"es",
"fr",
"hi",
"it",
"ja",
"ko",
"pl",
"pt",
"ru",
"tr",
"zh",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-to-speech | 2023-07-18T13:50:46Z | # Bark
Bark is a transformer-based text-to-audio model created by [Suno](https://www.suno.ai).
Bark can generate highly realistic, multilingual speech as well as other audio - including music,
background noise and simple sound effects. The model can also produce nonverbal
communications like laughing, sighing and c... | [] |
mradermacher/Megamind-v2-VL-high-i1-GGUF | mradermacher | 2026-04-26T00:07:30Z | 1,427 | 1 | transformers | [
"transformers",
"gguf",
"agent",
"en",
"base_model:digitranslab/Megamind-v2-VL-high",
"base_model:quantized:digitranslab/Megamind-v2-VL-high",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-01T15:05:26Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [
{
"start": 624,
"end": 651,
"text": "Megamind-v2-VL-high-i1-GGUF",
"label": "benchmark name",
"score": 0.7697123289108276
},
{
"start": 725,
"end": 749,
"text": "Megamind-v2-VL-high-GGUF",
"label": "benchmark name",
"score": 0.6481288075447083
},
{
"start": 871,
... |
Yiwen-ntu/MeshAnythingV2 | Yiwen-ntu | 2024-08-11T11:49:40Z | 8,010 | 22 | null | [
"safetensors",
"shape_opt",
"model_hub_mixin",
"pytorch_model_hub_mixin",
"image-to-3d",
"arxiv:2408.02555",
"license:mit",
"region:us"
] | image-to-3d | 2024-08-05T11:35:19Z | # MeshAnythingV2
Library: [https://github.com/buaacyw/MeshAnythingV2](https://github.com/buaacyw/MeshAnythingV2)
## Contents
- [Contents](#contents)
- [Installation](#installation)
- [Usage](#usage)
- [Important Notes](#important-notes)
- [Acknowledgement](#acknowledgement)
- [BibTeX](#bibtex)
## Installation
Our en... | [] |
bluryar/VoxCPM-GGUF | bluryar | 2026-04-21T01:45:24Z | 3,293 | 10 | null | [
"gguf",
"text-to-speech",
"base_model:openbmb/VoxCPM-0.5B",
"base_model:quantized:openbmb/VoxCPM-0.5B",
"endpoints_compatible",
"region:us"
] | text-to-speech | 2026-03-18T01:38:01Z | # VoxCPM.cpp
[](LICENSE)
Standalone C++ inference project for VoxCPM models built on top of `ggml`.
- **VoxCPM.CPP Repo**: https://github.com/bluryar/VoxCPM.cpp
- **GGUF Weights**: https://huggingface.co/bluryar/VoxCPM-GGUF
- VoxCPM Official Repos... | [] |
akh99/veena-hinglish | akh99 | 2026-01-21T18:01:12Z | 6,326 | 4 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-to-speech",
"tts",
"hinglish",
"speech-synthesis",
"snac",
"hi",
"en",
"dataset:akh99/indictts-hinglish",
"base_model:maya-research/Veena",
"base_model:finetune:maya-research/Veena",
"license:apache-2.0",
"text-generation... | text-to-speech | 2026-01-10T17:05:47Z | # Veena Hinglish TTS
Fine-tuned Veena TTS model for Hinglish (Hindi-English) speech synthesis.
**Performance on Hinglish(Hindi written in English)**: Base model MOS: 4.12/5 → Fine-tuned model: 4.66/5
## Model Description
Veena Hinglish is a LoRA fine-tuned text-to-speech model optimized for generating natural-sound... | [] |
Vishva007/Qwen3.5-0.8B-W4A16-AutoRound-AWQ | Vishva007 | 2026-03-09T10:14:36Z | 1,047 | 2 | null | [
"safetensors",
"qwen3_5",
"base_model:Qwen/Qwen3.5-0.8B",
"base_model:quantized:Qwen/Qwen3.5-0.8B",
"4-bit",
"awq",
"region:us"
] | null | 2026-03-03T16:34:06Z | # Vishva007/Qwen3.5-0.8B-W4A16-AutoRound-AWQ
This is a **W4A16 (4-bit weight, 16-bit activation) AWQ-format** quantized version of [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B), produced using [AutoRound](https://github.com/intel/auto-round) — Intel's sign gradient descent based quantization method des... | [] |
mradermacher/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored-GGUF | mradermacher | 2025-11-22T16:10:33Z | 332 | 1 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"finetune",
"en",
"base_model:DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored",
"base_model:quantized:DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored",
"endpoints_compatible",
"region:us",
"co... | null | 2025-11-22T07:02:30Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
Smoffyy/Qwen2.5-7B-Instruct-Pure-GGUF | Smoffyy | 2026-03-25T23:12:17Z | 2,985 | 2 | transformers | [
"transformers",
"gguf",
"PureGGUF",
"text-generation",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-7B",
"base_model:quantized:Qwen/Qwen2.5-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-08-18T23:12:17Z | # Pure Quantized versions from Official [Qwen 2.5 7B](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
<img width="900px" src="https://cdn-uploads.huggingface.co/production/uploads/648812cd28c3bccafcd68e4c/f_q_iFfEA0txQQtDuVRrF.png">
These are quantized versions of the official [Qwen 2.5 7B](https://huggingface.co/Q... | [] |
velyan/gemma-3n-E4B-it-Q4_K_M-GGUF | velyan | 2026-02-04T14:47:10Z | 173 | 1 | transformers | [
"transformers",
"gguf",
"automatic-speech-recognition",
"automatic-speech-translation",
"audio-text-to-text",
"video-text-to-text",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"base_model:google/gemma-3n-E4B-it",
"base_model:quantized:google/gemma-3n-E4B-it",
"license:gemma",
"endpoin... | image-text-to-text | 2025-07-17T08:16:34Z | # velyan/gemma-3n-E4B-it-Q4_K_M-GGUF
This model was converted to GGUF format from [`google/gemma-3n-E4B-it`](https://huggingface.co/google/gemma-3n-E4B-it) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.... | [] |
urchade/gliner_base | urchade | 2024-04-10T10:10:19Z | 3,264 | 84 | gliner | [
"gliner",
"pytorch",
"token-classification",
"en",
"dataset:Universal-NER/Pile-NER-type",
"arxiv:2311.08526",
"license:cc-by-nc-4.0",
"region:us"
] | token-classification | 2024-02-16T20:57:17Z | # Model Card for GLiNER-base
GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, des... | [] |
sentence-transformers/distiluse-base-multilingual-cased-v2 | sentence-transformers | 2025-03-06T13:31:55Z | 721,277 | 208 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"openvino",
"distilbert",
"feature-extraction",
"sentence-similarity",
"multilingual",
"ar",
"bg",
"ca",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"fi",
"fr",
"gl",
"gu",
"he",
"hi",
"hr",
... | sentence-similarity | 2022-03-02T23:29:05Z | # sentence-transformers/distiluse-base-multilingual-cased-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 512 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes... | [] |
mradermacher/Zoom-OCR-GGUF | mradermacher | 2026-02-04T09:56:09Z | 154 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:johnzqlu/Zoom-OCR",
"base_model:quantized:johnzqlu/Zoom-OCR",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-04T09:49:29Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-i1-GGUF | mradermacher | 2025-05-29T00:30:10Z | 185 | 1 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"llama-3",
"llama-3.2",
"en",
"base_model:DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B",
"base_model:quantized:DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B",
"endpoints_compatible",
"... | null | 2024-12-12T21:35:02Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B
<!-- provided-files -->... | [] |
mradermacher/mox-tiny-1-i1-GGUF | mradermacher | 2026-03-07T18:32:43Z | 7,244 | 4 | transformers | [
"transformers",
"gguf",
"conversational",
"conversational-ai",
"chat",
"helpful-ai",
"large-language-model",
"meta-llama",
"vanta-research",
"ai-persona-research",
"reasoning",
"cognitive",
"collaborative-ai",
"text-generation",
"roleplay",
"text-generation-inference",
"llama3.1",
... | text-generation | 2026-01-18T11:05:40Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
mradermacher/Qwen3-MOE-4x0.6B-2.4B-Writing-Thunder-V1.2-i1-GGUF | mradermacher | 2025-12-23T06:30:28Z | 119 | 1 | transformers | [
"transformers",
"gguf",
"programming",
"code generation",
"code",
"codeqwen",
"moe",
"coding",
"coder",
"qwen2",
"chat",
"qwen",
"qwen-coder",
"mixture of experts",
"4 experts",
"2 active experts",
"40k context",
"qwen3",
"finetune",
"qwen3_moe",
"creative",
"all use cases"... | null | 2025-08-27T20:17:43Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [
{
"start": 462,
"end": 504,
"text": "Qwen3-MOE-4x0.6B-2.4B-Writing-Thunder-V1.2",
"label": "benchmark name",
"score": 0.6123675107955933
}
] |
naver-hyperclovax/HyperCLOVAX-SEED-Text-Instruct-0.5B | naver-hyperclovax | 2025-07-21T15:13:41Z | 2,744 | 84 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-22T06:00:38Z | 
## Overview
HyperCLOVAX-SEED-Text-Instruct-0.5B is a Text-to-Text model with instruction-following capabilities that excels in understanding Korean language and culture. Compared to external competit... | [] |
DeverStyle/Flux.2-Klein-Loras | DeverStyle | 2026-04-12T10:07:00Z | 508 | 30 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:black-forest-labs/FLUX.2-klein-9B",
"base_model:adapter:black-forest-labs/FLUX.2-klein-9B",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-01-23T00:37:24Z | # Flux.2 Klein 9b Loras
To be used with the Flux.2 Klein 9b Distilled model.
<Gallery />
#### Slay The Spire 2 (events) style
Use `sts2_style` as the trigger word. For best results recommended to use with additional modifiers like "dark fantasy illustration". Trained on 55 game events artwork.
[More examples in thi... | [] |
unsloth/Qwen3-VL-2B-Thinking-1M-GGUF | unsloth | 2025-11-01T19:56:34Z | 485 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"image-text-to-text",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen3-VL-2B-Thinking",
"base_model:quantized:Qwen/Qwen3-VL-2B-Thinking",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"con... | image-text-to-text | 2025-10-31T13:04:31Z | > [!NOTE]
> Includes Unsloth **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
>
<div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
... | [] |
huihui-ai/Huihui-gpt-oss-20b-mxfp4-abliterated-v2 | huihui-ai | 2025-09-27T20:26:15Z | 1,831 | 17 | transformers | [
"transformers",
"safetensors",
"gguf",
"gpt_oss",
"text-generation",
"vllm",
"unsloth",
"abliterated",
"uncensored",
"conversational",
"base_model:huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated-v2",
"base_model:quantized:huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated-v2",
"license:apache-2.0",... | text-generation | 2025-09-27T14:42:57Z | # huihui-ai/Huihui-gpt-oss-20b-mxfp4-abliterated-v2
This is a mxfp4 version of [huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated-v2](https://huggingface.co/huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated-v2)
## QAT
Reference [OpenAI GPT-OSS Quantization Aware Training (QAT) & Quantized Deployment](https://github.com/NV... | [] |
bullerwins/Wan2.2-I2V-A14B-GGUF | bullerwins | 2025-07-28T18:02:35Z | 79,753 | 284 | null | [
"gguf",
"image-to-video",
"en",
"zh",
"arxiv:2503.20314",
"base_model:Wan-AI/Wan2.2-I2V-A14B",
"base_model:quantized:Wan-AI/Wan2.2-I2V-A14B",
"license:apache-2.0",
"region:us"
] | image-to-video | 2025-07-28T14:21:34Z | You need to download both a high-noise model and a low-noise model. High noise is used for the first steps and the low-noise for the details.
Place them on ComfyUI/models/unet
You will need [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) from [city96](https://github.com/city96)
Example workflow included in t... | [] |
ISxOdin/vit-base-oxford-iiit-pets | ISxOdin | 2025-04-11T14:11:40Z | 72,771 | 1 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"zero-shot-image-classification",
"base_model:google/vit-base-patch16-224",
"base_model:finetune:google/vit-base-patch16-224",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-04-01T15:21:11Z | # vit-base-oxford-iiit-pets
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the pcuenq/oxford-pets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1924
- Accuracy: 0.9445
## Model description
This model is a fine-... | [
{
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"end": 266,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.7989455461502075
},
{
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"end": 1608,
"text": "accuracy",
"label": "evaluation metric",
"score": 0.8281347751617432
},
{
"start": 1610,
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"text"... |
mradermacher/MediX-R1-8B-GGUF | mradermacher | 2026-03-01T08:53:46Z | 898 | 1 | transformers | [
"transformers",
"gguf",
"medical",
"reinforcement-learning",
"multimodal",
"vision-language",
"qwen3-vl",
"en",
"base_model:MBZUAI/MediX-R1-8B",
"base_model:quantized:MBZUAI/MediX-R1-8B",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us",
"conversational"
] | reinforcement-learning | 2026-02-28T12:47:48Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
timm/ViT-SO400M-14-SigLIP2 | timm | 2025-02-21T23:26:44Z | 34,629 | 1 | open_clip | [
"open_clip",
"safetensors",
"siglip",
"siglip2",
"vision",
"zero-shot-image-classification",
"dataset:webli",
"arxiv:2502.14786",
"arxiv:2303.15343",
"license:apache-2.0",
"region:us"
] | zero-shot-image-classification | 2025-02-21T17:01:57Z | # Model card for ViT-SO400M-14-SigLIP2
## Model Details
A SigLIP 2 Vision-Lanuage model trained on WebLI.
This model has been converted for use in OpenCLIP from the original JAX checkpoints in [Big Vision](https://github.com/google-research/big_vision).
## Model Details
- **Model Type:** Contrastive Image-Text, Zer... | [] |
TeddyBell001/arxiv-scibert-11class | TeddyBell001 | 2026-04-08T23:30:28Z | 151 | 1 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:allenai/scibert_scivocab_cased",
"base_model:finetune:allenai/scibert_scivocab_cased",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-08T19:01:07Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# arxiv-scibert-11class
This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibe... | [
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"label": "evaluation metric",
"score": 0.707779586315155
},
{
"start": 434,
"end": 442,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.9373922348022461
},
{
"start": 444,
"end": 450,
"text": "0.79... |
emrecan/bert-base-turkish-cased-mean-nli-stsb-tr | emrecan | 2025-12-26T21:47:05Z | 100,845 | 49 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"tr",
"dataset:nli_tr",
"dataset:emrecan/stsb-mt-turkish",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us",
"deploy:azure"
] | sentence-similarity | 2022-03-02T23:29:05Z | # emrecan/bert-base-turkish-cased-mean-nli-stsb-tr
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. The model was trained on Turkish machine translated versions of [NLI](h... | [] |
microsoft/swin-base-patch4-window12-384 | microsoft | 2022-05-16T18:32:57Z | 3,537 | 5 | transformers | [
"transformers",
"pytorch",
"tf",
"swin",
"image-classification",
"vision",
"dataset:imagenet-1k",
"arxiv:2103.14030",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | image-classification | 2022-03-02T23:29:05Z | # Swin Transformer (base-sized model)
Swin Transformer model trained on ImageNet-1k at resolution 384x384. It was introduced in the paper [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030) by Liu et al. and first released in [this repository](https://github.com... | [] |
mradermacher/Dans-PersonalityEngine-V1.3.0-24b-absolute-heresy-GGUF | mradermacher | 2026-02-01T12:03:55Z | 279 | 1 | transformers | [
"transformers",
"gguf",
"general-purpose",
"roleplay",
"storywriting",
"chemistry",
"biology",
"code",
"climate",
"axolotl",
"text-generation-inference",
"finetune",
"legal",
"medical",
"finance",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"ar",
"de",
"fr... | null | 2026-02-01T09:55:34Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
KORMo-Team/KORMo-10B-base | KORMo-Team | 2026-03-18T18:54:11Z | 137 | 38 | transformers | [
"transformers",
"safetensors",
"kormo",
"text-generation",
"custom_code",
"arxiv:2510.09426",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-10-11T17:01:23Z | <!-- <p align="center">
<img src="https://github.com/MLP-Lab/KORMo-tutorial/blob/main/tutorial/attachment/kormo_logo.png?raw=true" style="width: 100%; max-width: 1100px;">
</p> -->
<p align="center">
<img src="https://github.com/MLP-Lab/KORMo-tutorial/blob/main/tutorial/attachment/kormo_logo.svg?raw=true" style="w... | [] |
mlx-community/phi-2 | mlx-community | 2024-08-15T16:52:38Z | 388 | 55 | mlx | [
"mlx",
"phi-msft",
"nlp",
"code",
"text-generation",
"en",
"base_model:microsoft/phi-2",
"base_model:finetune:microsoft/phi-2",
"license:other",
"region:us"
] | text-generation | 2023-12-19T16:45:41Z | ## Model Summary
Phi-2 is a Transformer with **2.7 billion** parameters. It was trained using the same data sources as [Phi-1.5](https://huggingface.co/microsoft/phi-1.5), augmented with a new data source that consists of various NLP synthetic texts and filtered websites (for safety and educational value). When assess... | [
{
"start": 18,
"end": 23,
"text": "Phi-2",
"label": "benchmark name",
"score": 0.8197159171104431
},
{
"start": 121,
"end": 128,
"text": "Phi-1.5",
"label": "benchmark name",
"score": 0.7786897420883179
},
{
"start": 163,
"end": 170,
"text": "phi-1.5",
... |
SamsungSAILMontreal/Qwen3-30B-A3B-Instruct-2507-REAM | SamsungSAILMontreal | 2026-04-08T16:50:44Z | 184 | 7 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"compression",
"expert-merging",
"moe",
"conversational",
"arxiv:2604.04356",
"base_model:Qwen/Qwen3-30B-A3B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-30B-A3B-Instruct-2507",
"license:apache-2.0",
"endpoints_compatible",
... | text-generation | 2026-01-14T17:02:28Z | arXiv: [REAM: Merging Improves Pruning of Experts in LLMs](https://arxiv.org/abs/2604.04356)
# Qwen3-30B-A3B-Instruct-2507-REAM
This model is a compressed version of [Qwen/Qwen3-30B-A3B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507).
It is obtained by reducing the number of experts in each M... | [
{
"start": 1452,
"end": 1457,
"text": "GSM8K",
"label": "benchmark name",
"score": 0.6061925888061523
}
] |
squ11z1/DeepSeek-R1-Opus | squ11z1 | 2026-02-27T00:47:51Z | 964 | 2 | null | [
"safetensors",
"gguf",
"alignment",
"bloom-evaluation",
"lora",
"deepseek",
"safety",
"unsloth",
"text-generation",
"conversational",
"en",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"license:mit",
"endpoints_co... | text-generation | 2026-02-26T21:53:28Z | # DeepSeek-R1-Opus
An alignment-focused fine-tune of [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B). Alignment improvements are measured transparent... | [
{
"start": 175,
"end": 204,
"text": "DeepSeek-R1-Distill-Qwen-1.5B",
"label": "benchmark name",
"score": 0.6456546783447266
},
{
"start": 341,
"end": 346,
"text": "Bloom",
"label": "benchmark name",
"score": 0.8300223350524902
},
{
"start": 496,
"end": 501,
... |
baa-ai/Qwen3.5-122B-A10B-RAM-48GB-MLX | baa-ai | 2026-04-16T11:37:10Z | 4,129 | 6 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"quantized",
"mixed-precision",
"qwen3.5",
"moe",
"base_model:Qwen/Qwen3.5-122B-A10B",
"base_model:quantized:Qwen/Qwen3.5-122B-A10B",
"license:other",
"4-bit",
"region:us"
] | null | 2026-04-06T00:19:35Z | # Qwen3.5-122B-A10B — 46 GB (MLX)
Mixed-precision quantized version of [Qwen/Qwen3.5-122B-A10B](https://huggingface.co/Qwen/Qwen3.5-122B-A10B) optimised by [baa.ai](https://baa.ai) using a proprietary Black Sheep AI method.
Per-tensor bit-width allocation via advanced sensitivity analysis and budget-const... | [
{
"start": 1170,
"end": 1178,
"text": "Shepherd",
"label": "benchmark name",
"score": 0.619459331035614
}
] |
mradermacher/llama-3.1-8b-russian-alpaca-i1-GGUF | mradermacher | 2026-01-04T02:16:49Z | 173 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"en",
"base_model:9re90r1/llama-3.1-8b-russian-alpaca",
"base_model:quantized:9re90r1/llama-3.1-8b-russian-alpaca",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-04T01:22:46Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [
{
"start": 627,
"end": 662,
"text": "llama-3.1-8b-russian-alpaca-i1-GGUF",
"label": "benchmark name",
"score": 0.615911066532135
}
] |
aari1995/German_Semantic_V3 | aari1995 | 2024-09-12T13:05:19Z | 404 | 18 | sentence-transformers | [
"sentence-transformers",
"onnx",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"loss:MatryoshkaLoss",
"custom_code",
"de",
"base_model:aari1995/gbert-large-2",
"base_model:quantized:aari1995/gbert-large-2",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints... | sentence-similarity | 2024-06-23T16:06:10Z | # 🇩🇪 German Semantic V3 🇩🇪
### (and [**German_Semantic_V3b**](https://huggingface.co/aari1995/German_Semantic_V3b))
The successors of [German_Semantic_STS_V2](https://huggingface.co/aari1995/German_Semantic_STS_V2) are here and come with loads of cool new features! While V3 is really knowledge-heavy, [German_Seman... | [] |
stepfun-ai/GOT-OCR-2.0-hf | stepfun-ai | 2025-01-31T16:40:29Z | 37,370 | 227 | transformers | [
"transformers",
"safetensors",
"got_ocr2",
"image-text-to-text",
"got",
"vision-language",
"ocr2.0",
"multilingual",
"arxiv:2409.01704",
"arxiv:2405.14295",
"arxiv:2312.06109",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2024-11-22T23:01:40Z | <h1>General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model - HF Transformers 🤗 implementation
</h1>
[🤗 Spaces Demo](https://huggingface.co/spaces/yonigozlan/GOT-OCR-Transformers) | [🌟GitHub](https://github.com/Ucas-HaoranWei/GOT-OCR2.0/) | [📜Paper](https://arxiv.org/abs/2409.01704)</a>
[Haoran Wei*]... | [] |
internlm/Intern-S1-mini | internlm | 2026-03-29T04:49:52Z | 2,710 | 114 | transformers | [
"transformers",
"safetensors",
"interns1",
"text-generation",
"image-text-to-text",
"conversational",
"custom_code",
"arxiv:2508.15763",
"license:apache-2.0",
"region:us"
] | image-text-to-text | 2025-08-18T06:32:48Z | ## Intern-S1-mini
<div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/642695e5274e7ad464c8a5ba/E43cgEXBRWjVJlU_-hdh6.png" />
<div> </div>
[💻Github Repo](https://github.com/InternLM/Intern-S1) • [🤗Model Collections](https://huggingface.co/collections/internlm/intern-s1-6882e3... | [] |
Mungert/pokee_research_7b-GGUF | Mungert | 2025-11-01T04:39:10Z | 384 | 1 | transformers | [
"transformers",
"gguf",
"agent",
"deepresearch",
"llm",
"rl",
"reinforcementlearning",
"text-generation",
"en",
"dataset:miromind-ai/MiroRL-GenQA",
"arxiv:2510.15862",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"endpoints... | text-generation | 2025-10-26T14:15:31Z | # <span style="color: #7FFF7F;">pokee_research_7b GGUF Models</span>
## <span style="color: #7F7FFF;">Model Generation Details</span>
This model was generated using [llama.cpp](https://github.com/ggerganov/llama.cpp) at commit [`16724b5b6`](https://github.com/ggerganov/llama.cpp/commit/16724b5b6836a2d4b8936a5824d2ff... | [] |
mradermacher/Olmo-3-7B-Think-SFT-GGUF | mradermacher | 2025-11-25T00:19:09Z | 181 | 1 | transformers | [
"transformers",
"gguf",
"en",
"dataset:allenai/Dolci-Think-SFT-7B",
"base_model:allenai/Olmo-3-7B-Think-SFT",
"base_model:quantized:allenai/Olmo-3-7B-Think-SFT",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-20T23:06:11Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
DavidAU/Qwen3.5-9B-Claude-4.6-OS-Auto-Variable-THINKING | DavidAU | 2026-03-13T01:19:53Z | 217 | 2 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"unsloth",
"fine tune",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"romance",
... | image-text-to-text | 2026-03-06T01:43:33Z | <h2>Qwen3.5-9B-Claude-4.6-OS-Auto-Variable-THINKING</h2>
Fine tune via Unsloth of Qwen 3.5 9B dense model using Claude-4.6-OS dataset (4 Claude datasets) on local hardware.
This has altered reasoning/thinking block as well as thinking/reasoning block size. (reduced / improved)
Every attempt was made to ensure the tr... | [
{
"start": 4,
"end": 51,
"text": "Qwen3.5-9B-Claude-4.6-OS-Auto-Variable-THINKING",
"label": "benchmark name",
"score": 0.6534644365310669
},
{
"start": 637,
"end": 656,
"text": "Qwen3.5-9B-Thinking",
"label": "benchmark name",
"score": 0.7683799266815186
}
] |
cerebras/DeepSeek-V3.2-REAP-508B-A37B | cerebras | 2025-12-09T14:34:09Z | 1,275 | 16 | transformers | [
"transformers",
"safetensors",
"deepseek_v3",
"text-generation",
"deepseek",
"MOE",
"pruning",
"compression",
"en",
"arxiv:2510.13999",
"base_model:deepseek-ai/DeepSeek-V3.2",
"base_model:quantized:deepseek-ai/DeepSeek-V3.2",
"license:mit",
"text-generation-inference",
"endpoints_compati... | text-generation | 2025-12-09T14:28:59Z | <p align="center">
<em>𓌳 <strong>REAP</strong>𓌳 the Experts: Why Pruning Prevails for One-Shot MoE Compression</em><br>
<img src="https://i.imgur.com/rmzG3gg.png" alt="REAP" width="75%">
</p>
# DeepSeek-V3.2-REAP-508B-A37B
## ✨ Highlights
Introducing **DeepSeek-V3.2-REAP-508B-A37B**, a **memory-efficient comp... | [] |
mradermacher/Qwen3-MOE-4x0.6B-2.4B-Writing-Thunder-V1.2-GGUF | mradermacher | 2025-08-27T20:57:06Z | 116 | 1 | transformers | [
"transformers",
"gguf",
"programming",
"code generation",
"code",
"codeqwen",
"moe",
"coding",
"coder",
"qwen2",
"chat",
"qwen",
"qwen-coder",
"mixture of experts",
"4 experts",
"2 active experts",
"40k context",
"qwen3",
"finetune",
"qwen3_moe",
"creative",
"all use cases"... | null | 2025-08-27T17:27:37Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
unsloth/granite-4.0-h-1b-GGUF | unsloth | 2025-10-28T11:29:21Z | 1,389 | 14 | transformers | [
"transformers",
"gguf",
"language",
"unsloth",
"granite-4.0",
"arxiv:0000.00000",
"base_model:ibm-granite/granite-4.0-h-1b",
"base_model:quantized:ibm-granite/granite-4.0-h-1b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-28T11:11:41Z | <div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
<div style="display: flex; gap: 5px; align-items: center; ">
<a href="https://github.com/u... | [] |
openvla/openvla-7b | openvla | 2026-02-17T03:43:23Z | 1,506,136 | 194 | transformers | [
"transformers",
"safetensors",
"openvla",
"feature-extraction",
"robotics",
"vla",
"image-text-to-text",
"multimodal",
"pretraining",
"custom_code",
"en",
"arxiv:2406.09246",
"license:mit",
"region:us"
] | robotics | 2024-06-10T16:35:59Z | # OpenVLA 7B
OpenVLA 7B (`openvla-7b`) is an open vision-language-action model trained on 970K robot manipulation episodes from the [Open X-Embodiment](https://robotics-transformer-x.github.io/) dataset.
The model takes language instructions and camera images as input and generates robot actions. It supports controll... | [] |
KiteFishAI/Minnow-Math-1.5B | KiteFishAI | 2026-02-28T12:01:37Z | 272,448 | 1 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"causal-lm",
"scientific-language-model",
"mathematics",
"arxiv",
"research",
"en",
"arxiv:2602.17288",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-12T11:54:16Z | # Minnow-Math-1.5B
**Minnow-Math-1.5B** is a ~1.5B parameter decoder-only transformer trained from scratch on raw arXiv LaTeX sources across mathematics, computer science, and theoretical physics.
📄 **Paper:** https://arxiv.org/abs/2602.17288
💻 **Github:** https://github.com/kitefishai/Minnow-Math-1.5B
This is a... | [
{
"start": 2,
"end": 18,
"text": "Minnow-Math-1.5B",
"label": "benchmark name",
"score": 0.9335169196128845
},
{
"start": 22,
"end": 38,
"text": "Minnow-Math-1.5B",
"label": "benchmark name",
"score": 0.9164422154426575
},
{
"start": 291,
"end": 307,
"text... |
sphaela/gemma-4-E4B-it-AutoRound-GGUF | sphaela | 2026-04-24T15:03:39Z | 929 | 1 | null | [
"gguf",
"auto-round",
"intel",
"quantization",
"vlm",
"multilingual",
"base_model:google/gemma-4-E4B-it",
"base_model:quantized:google/gemma-4-E4B-it",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-17T12:40:36Z | # Gemma-4-E4B-it GGUF (AutoRound Quantized)
This repository contains GGUF quantized versions of [google/gemma-4-E4B-it](https://huggingface.co/google/gemma-4-E4B-it) created using Intel's [AutoRound](https://github.com/intel/auto-round) quantization method.
## Quantization Details
The models were quantized using var... | [] |
dx8152/Qwen-Image-Edit-2509-White_film_to_rendering | dx8152 | 2025-11-12T09:53:47Z | 2,230 | 48 | diffusers | [
"diffusers",
"image-to-image",
"base_model:Qwen/Qwen-Image-Edit",
"base_model:finetune:Qwen/Qwen-Image-Edit",
"license:apache-2.0",
"region:us"
] | image-to-image | 2025-10-26T01:29:20Z | Welcome everyone to use Lora in Qwen-Edit for Image Fusion. It's an excellent performer!
***2509 is not very compatible with this lora, it is recommended to use Qwen-Edit***
Trigger Words:白膜转材质
Instructions: Download the Lora file to the models/loras folder.
You'll also need this Lora to use it: https://huggingface... | [] |
cja5553/xlm-roberta-Twitter-spam-classification | cja5553 | 2024-11-28T06:22:59Z | 196 | 1 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"Twitter",
"Spam detection",
"en",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2024-11-09T08:38:14Z | # Spam detection of Tweets
This model classifies Tweets from X (formerly known as Twitter) into 'Spam' (1) or 'Quality' (0).
## Training Dataset
This was finetuned on the [UtkMl's Twitter Spam Detection dataset](https://www.kaggle.com/c/twitter-spam/overview) with [`FacebookAI/xlm-roberta-large`](https://huggingface... | [
{
"start": 97,
"end": 101,
"text": "Spam",
"label": "evaluation metric",
"score": 0.6866859793663025
},
{
"start": 111,
"end": 118,
"text": "Quality",
"label": "evaluation metric",
"score": 0.8021130561828613
},
{
"start": 660,
"end": 667,
"text": "Quality... |
Kamtera/persian-tts-female-vits | Kamtera | 2023-03-19T07:32:31Z | 174 | 21 | TTS | [
"TTS",
"tensorboard",
"Persian",
"Farsi",
"Coqui",
"CoquiTTS",
"pytorch",
"audio",
"text-to-speech",
"fa",
"dataset:persian-tts-dataset",
"license:openrail",
"region:us"
] | text-to-speech | 2023-01-14T09:31:36Z | # **persian-tts-female-vits**
- persian-tts-female vits model for text to speech purposes.
- Persian فارسی
- Single-speaker female voice
- Trained on <span style="color: #0072ff;font-weight: bold;">[persian-tts-dataset-male](https://www.kaggle.com/datasets/magnoliasis/persian-tts-dataset-famale)</span> dataset
- [Gi... | [] |
ibm-granite/granite-guardian-hap-125m | ibm-granite | 2024-12-19T19:53:49Z | 1,941 | 28 | transformers | [
"transformers",
"pytorch",
"safetensors",
"roberta",
"text-classification",
"en",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-classification | 2024-09-05T17:17:39Z | ## Granite-Guardian-HAP-125m
## Model Summary
This model is IBM's 12-layer toxicity binary classifier for English, intended to be used as a guardrail for any large language model. It has been trained on several benchmark datasets in English, specifically for detecting hateful, abusive, profane and other toxic content ... | [
{
"start": 3,
"end": 28,
"text": "Granite-Guardian-HAP-125m",
"label": "benchmark name",
"score": 0.9308400750160217
},
{
"start": 733,
"end": 758,
"text": "granite-guardian-hap-125m",
"label": "benchmark name",
"score": 0.9183034300804138
},
{
"start": 1269,
... |
tiiuae/Falcon-H1-Tiny-Tool-Calling-90M-GGUF | tiiuae | 2026-01-15T19:56:45Z | 309 | 5 | transformers | [
"transformers",
"gguf",
"falcon-h1",
"edge",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-13T06:53:37Z | <img src="https://cdn-uploads.huggingface.co/production/uploads/62441d1d9fdefb55a0b7d12c/l1du02RjuAZJcksI5tQ-F.png" alt="drawing" width="800"/>
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Training Details](#training-details)
3. [Usage](#usage)
4. [Evaluation](#evaluation)
5. [Citati... | [] |
Qwen/Qwen2.5-7B | Qwen | 2024-09-25T12:32:32Z | 1,061,141 | 267 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"arxiv:2407.10671",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-generation | 2024-09-15T12:17:40Z | # Qwen2.5-7B
## Introduction
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
- Significantly **more knowledge** a... | [] |
ZuluVision/MoviiGen1.1 | ZuluVision | 2025-06-18T08:06:52Z | 319 | 104 | diffusers | [
"diffusers",
"safetensors",
"t2v",
"video generation",
"text-to-video",
"en",
"base_model:Wan-AI/Wan2.1-T2V-14B",
"base_model:finetune:Wan-AI/Wan2.1-T2V-14B",
"license:apache-2.0",
"region:us"
] | text-to-video | 2025-05-12T12:48:39Z | # MoviiGen 1.1
<span>[](https://huggingface.co/ZuluVision/MoviiGen1.1)</span> <span>[](https://github.com/ZulutionAI/MoviiGen1.1/stargazers)</span>
[**Movi... | [] |
kristaller486/dots.ocr-1.5 | kristaller486 | 2026-02-18T10:36:39Z | 149,923 | 20 | dots_ocr_1_5 | [
"dots_ocr_1_5",
"safetensors",
"dots_ocr",
"text-generation",
"image-to-text",
"ocr",
"document-parse",
"layout",
"table",
"formula",
"transformers",
"custom_code",
"image-text-to-text",
"conversational",
"en",
"zh",
"multilingual",
"license:mit",
"region:us"
] | image-text-to-text | 2026-02-18T10:29:45Z | ## The model was removed from huggingface, so I re-uploaded it here from modelscope repo (the MIT license allows this).
<div align="center">
<p align="center">
<img src="https://raw.githubusercontent.com/rednote-hilab/dots.ocr/master/assets/logo.png" width="300"/>
<p>
<h1 align="center">
dots.ocr-1.5: Recognize ... | [] |
Alibaba-NLP/Tongyi-DeepResearch-30B-A3B | Alibaba-NLP | 2025-10-10T11:39:33Z | 17,578 | 807 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"conversational",
"en",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-generation | 2025-09-16T06:56:49Z | # Introduction
We present **Tongyi DeepResearch**, an agentic large language model featuring 30 billion total parameters, with only 3 billion activated per token. Developed by Tongyi Lab, the model is specifically designed for **long-horizon, deep information-seeking** tasks. Tongyi-DeepResearch demonstrates state-of... | [
{
"start": 30,
"end": 49,
"text": "Tongyi DeepResearch",
"label": "benchmark name",
"score": 0.7798653841018677
},
{
"start": 418,
"end": 429,
"text": "BrowserComp",
"label": "benchmark name",
"score": 0.6503536105155945
},
{
"start": 431,
"end": 445,
"tex... |
bartowski/allenai_Olmo-3.1-32B-Think-GGUF | bartowski | 2025-12-12T23:03:45Z | 4,516 | 3 | null | [
"gguf",
"text-generation",
"en",
"dataset:allenai/Dolci-Think-RL",
"base_model:allenai/Olmo-3.1-32B-Think",
"base_model:quantized:allenai/Olmo-3.1-32B-Think",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | text-generation | 2025-12-12T18:11:57Z | ## Llamacpp imatrix Quantizations of Olmo-3.1-32B-Think by allenai
Using <a href="https://github.com/ggml-org/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggml-org/llama.cpp/releases/tag/b7340">b7340</a> for quantization.
Original model: https://huggingface.co/allenai/Olmo-3.1-32B-Think
All quants m... | [] |
google/bigbird-roberta-base | google | 2021-06-02T14:30:54Z | 217,759 | 62 | transformers | [
"transformers",
"pytorch",
"jax",
"big_bird",
"pretraining",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"dataset:cc_news",
"arxiv:2007.14062",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05Z | # BigBird base model
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
It is a pretrained model o... | [] |
second-state/stable-diffusion-v1-5-GGUF | second-state | 2024-11-22T06:47:59Z | 19,885 | 26 | null | [
"gguf",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"base_model:runwayml/stable-diffusion-v1-5",
"base_model:quantized:runwayml/stable-diffusion-v1-5",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2024-07-09T14:30:10Z | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
<!-- header ... | [] |
mradermacher/DAC5-3B-i1-GGUF | mradermacher | 2026-02-21T03:00:44Z | 107 | 1 | transformers | [
"transformers",
"gguf",
"DAC",
"M.INC.",
"conversational",
"it",
"en",
"dataset:Mattimax/DACMini_Refined",
"dataset:Mattimax/Camoscio-ITA",
"base_model:Mattimax/DAC5-3B",
"base_model:quantized:Mattimax/DAC5-3B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2026-02-21T01:29:32Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [
{
"start": 608,
"end": 623,
"text": "DAC5-3B-i1-GGUF",
"label": "benchmark name",
"score": 0.6017831563949585
}
] |
mradermacher/Rocinante-X-12B-v1-Heretic-Uncensored-i1-GGUF | mradermacher | 2026-01-28T09:05:34Z | 813 | 2 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"finetune",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"romance"... | null | 2026-01-28T07:20:10Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [
{
"start": 637,
"end": 682,
"text": "Rocinante-X-12B-v1-Heretic-Uncensored-i1-GGUF",
"label": "benchmark name",
"score": 0.7289494276046753
},
{
"start": 756,
"end": 798,
"text": "Rocinante-X-12B-v1-Heretic-Uncensored-GGUF",
"label": "benchmark name",
"score": 0.662064015... |
fal/AuraFlow | fal | 2024-07-18T05:24:00Z | 243 | 656 | diffusers | [
"diffusers",
"safetensors",
"text-to-image",
"license:apache-2.0",
"diffusers:AuraFlowPipeline",
"region:us"
] | text-to-image | 2024-07-11T23:32:38Z | # AuraFlow
AuraFlow v0.1 is the fully open-sourced largest flow-based text-to-image generation model.
This model achieves state-of-the-art results on GenEval. Read our [blog post](https://blog.fal.... | [
{
"start": 273,
"end": 280,
"text": "GenEval",
"label": "benchmark name",
"score": 0.6337750554084778
}
] |
EleutherAI/pythia-160m | EleutherAI | 2023-07-09T15:52:09Z | 3,093,829 | 40 | transformers | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"pythia",
"en",
"dataset:EleutherAI/pile",
"arxiv:2304.01373",
"arxiv:2101.00027",
"arxiv:2201.07311",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"reg... | text-generation | 2023-02-08T19:25:46Z | The *Pythia Scaling Suite* is a collection of models developed to facilitate
interpretability research [(see paper)](https://arxiv.org/pdf/2304.01373.pdf).
It contains two sets of eight models of sizes
70M, 160M, 410M, 1B, 1.4B, 2.8B, 6.9B, and 12B. For each size, there are two
models: one trained on the Pile, and ... | [
{
"start": 5,
"end": 11,
"text": "Pythia",
"label": "benchmark name",
"score": 0.8544356822967529
},
{
"start": 573,
"end": 579,
"text": "Pythia",
"label": "benchmark name",
"score": 0.8413132429122925
},
{
"start": 1099,
"end": 1105,
"text": "Pythia",
... |
darkc0de/XORTRON.CriminalComputing.LARGE.2026.3-i1-GGUF | darkc0de | 2026-03-17T07:15:14Z | 519 | 2 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"fr",
"de",
"es",
"it",
"pt",
"zh",
"ja",
"ru",
"ko",
"base_model:darkc0de/XORTRON.CriminalComputing.LARGE.2026.3",
"base_model:quantized:darkc0de/XORTRON.CriminalComputing.LARGE.2026.3",
"license... | null | 2026-03-17T07:15:13Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
llmfan46/Qwen3.6-27B-uncensored-heretic-v2 | llmfan46 | 2026-05-03T03:44:10Z | 1,677 | 9 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"heretic",
"uncensored",
"decensored",
"abliterated",
"mpoa",
"conversational",
"base_model:Qwen/Qwen3.6-27B",
"base_model:finetune:Qwen/Qwen3.6-27B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-28T23:41:48Z | <div style="background-color: #ff4444; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
<h2 style="color: white; margin: 0 0 10px 0;">🚨⚠️ I HAVE REACHED HUGGING FACE'S FREE STORAGE LIMIT ⚠️🚨</h2>
<p style="font-size: 18px; margin: 0 0 15px 0;">I can no longer upload new models u... | [] |
QuantFactory/Mistral-Nemo-12B-ArliAI-RPMax-v1.2-GGUF | QuantFactory | 2024-10-16T03:56:59Z | 3,317 | 6 | null | [
"gguf",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2024-10-16T02:23:43Z | ---
license: apache-2.0
---
[](https://hf.co/QuantFactory)
# Q... | [] |
mradermacher/Qwen3-VL-8B-Instruct-Heretic-i1-GGUF | mradermacher | 2026-02-05T11:24:03Z | 16,622 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:jKqfO84n/Qwen3-VL-8B-Instruct-Heretic",
"base_model:quantized:jKqfO84n/Qwen3-VL-8B-Instruct-Heretic",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-11-21T02:23:31Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
Verdugie/Opus-Candid-27B-V3 | Verdugie | 2026-03-21T20:54:23Z | 313 | 1 | transformers | [
"transformers",
"gguf",
"conversational",
"personality",
"anti-sycophancy",
"bilingual",
"claude-distillation",
"opus",
"zipf-weighted",
"27b-dense",
"text-generation",
"en",
"es",
"base_model:Qwen/Qwen3.5-27B",
"base_model:quantized:Qwen/Qwen3.5-27B",
"license:apache-2.0",
"endpoint... | text-generation | 2026-03-07T02:06:04Z | # can·did
/ˈkandəd/ — truthful and straightforward; frank.
*From Latin candidus, meaning white, pure, sincere. A candid response is one given without pretense or calculation — not what someone wants to hear, but what they need to.*
## Opus-Candid-27B V3
The flagship. Fine-tuned from **Qwen 3.5 27B Dense** on **1,508 ... | [] |
JANGQ-AI/Qwen3.6-35B-A3B-JANGTQ | JANGQ-AI | 2026-04-17T05:36:26Z | 1,984 | 4 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"quantized",
"apple-silicon",
"qwen3",
"moe",
"vision",
"hybrid-attention",
"gated-deltanet",
"turboquant",
"jangtq",
"jangtq2",
"image-text-to-text",
"conversational",
"en",
"base_model:Qwen/Qwen3.6-35B-A3B",
"base_model:finetune:Qwen/Qwen3.6-3... | image-text-to-text | 2026-04-17T05:30:57Z | <p align="center">
<a href="https://osaurus.ai"><img src="./osaurus-x-banner.png" alt="Osaurus AI"></a>
</p>
<h3 align="center">Qwen 3.6 35B-A3B — JANGTQ2 (MLX)</h3>
<p align="center">TurboQuant codebook quantization of Alibaba's hybrid linear/full-attention agentic MoE — routed experts at 2-bit via Lloy... | [] |
mradermacher/Stentor-30M-GGUF | mradermacher | 2026-02-21T12:33:46Z | 234 | 3 | transformers | [
"transformers",
"gguf",
"text-generation",
"llama",
"small-language-model",
"efficient",
"edge-deployment",
"speculative-decoding",
"tiny-model",
"30m-parameters",
"kaggle-trained",
"educational",
"research",
"low-resource",
"cpu-inference",
"mobile-deployment",
"synthetic-data",
"... | text-generation | 2026-02-20T19:28:36Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [
{
"start": 512,
"end": 528,
"text": "Stentor-30M-GGUF",
"label": "benchmark name",
"score": 0.6002188920974731
}
] |
NewenAI/QuettaLLMs-27B-Koreasoner-V3 | NewenAI | 2026-04-16T07:21:55Z | 132 | 3 | null | [
"safetensors",
"qwen3_5",
"en",
"ko",
"base_model:Qwen/Qwen3.5-27B",
"base_model:finetune:Qwen/Qwen3.5-27B",
"license:apache-2.0",
"region:us"
] | null | 2026-04-07T09:02:46Z | # QuettaLLMs-27B-Koreasoner-V3
## Model Overview
**QuettaLLMs-27B-Koreasoner-V3** is a Korean large language model (LLM) fine-tuned using data refined by NewenAI. Built on the `Qwen/Qwen3.5-27B` base model, it underwent LoRA-based fine-tuning to improve its logical reasoning performance.
A notable feature of this mod... | [
{
"start": 2,
"end": 30,
"text": "QuettaLLMs-27B-Koreasoner-V3",
"label": "benchmark name",
"score": 0.8017037510871887
},
{
"start": 52,
"end": 80,
"text": "QuettaLLMs-27B-Koreasoner-V3",
"label": "benchmark name",
"score": 0.78749018907547
},
{
"start": 1036,
... |
lerobot/xvla-libero | lerobot | 2026-01-22T09:15:34Z | 7,490 | 4 | lerobot | [
"lerobot",
"safetensors",
"vision-language-action",
"imitation-learning",
"robotics",
"en",
"dataset:HuggingFaceVLA/libero",
"arxiv:2510.10274",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-02T15:47:18Z | # X-VLA (LeRobot)
X-VLA is a Vision-Language-Action foundation model that uses soft prompts to handle cross-embodiment and cross-domain robot control within a unified Transformer architecture.
Checkpoint trained and evaluated on LIBERO tasks.
**Original paper:** [X-VLA: Soft-Prompted Transformer as Scalable Cross-Em... | [] |
allenai/Olmo-3-7B-Instruct | allenai | 2026-01-05T16:23:38Z | 99,591 | 123 | transformers | [
"transformers",
"safetensors",
"olmo3",
"text-generation",
"conversational",
"en",
"dataset:allenai/Dolci-Instruct-RL-7B",
"arxiv:2512.13961",
"base_model:allenai/Olmo-3-7B-Instruct-DPO",
"base_model:finetune:allenai/Olmo-3-7B-Instruct-DPO",
"license:apache-2.0",
"endpoints_compatible",
"dep... | text-generation | 2025-11-19T20:49:53Z | ## Model Details
<img alt="Logo for Olmo 3 7B Instruct model" src="olmo-instruct.png" width="307px" style="margin-left:'auto' margin-right:'auto' display:'block'">
# Model Card for Olmo 3 7B Instruct
We introduce Olmo 3, a new family of 7B and 32B models both Instruct and Think variants. Long chain-of-thought thinki... | [] |
mradermacher/Huihui-Qwen3-30B-A3B-Instruct-2507-RP-i1-GGUF | mradermacher | 2026-02-02T21:25:12Z | 279 | 1 | transformers | [
"transformers",
"gguf",
"en",
"dataset:Gryphe/Sonnet3.5-Charcard-Roleplay",
"base_model:thaddeusk/Huihui-Qwen3-30B-A3B-Instruct-2507-RP",
"base_model:quantized:thaddeusk/Huihui-Qwen3-30B-A3B-Instruct-2507-RP",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"... | null | 2026-02-02T16:44:09Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
MaddoggProduction/whisper-l-v3-turbo-quran-lora-dataset-mix | MaddoggProduction | 2026-03-23T18:42:29Z | 864 | 15 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"Quran",
"Tajweed",
"Recitation",
"Islam",
"Arabic",
"turbo",
"ar",
"dataset:tarteel-ai/everyayah",
"dataset:MohamedRashad/Quran-Recitations",
"dataset:ahishamm/QURANICWhisperDataset",
"base_model:openai/whisper-la... | automatic-speech-recognition | 2026-02-17T19:50:43Z | # Whisper Large v3 Turbo Quran (LoRA Fine-Tuned)
This is a specialized **Automatic Speech Recognition (ASR)** model for **Quranic Recitation** with **tashkeel** or **diacritics**. It is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo), optimized to recognize... | [
{
"start": 458,
"end": 473,
"text": "Word Error Rate",
"label": "evaluation metric",
"score": 0.7108006477355957
}
] |
google/pegasus-cnn_dailymail | google | 2023-01-24T16:42:26Z | 10,626 | 110 | transformers | [
"transformers",
"pytorch",
"rust",
"pegasus",
"text2text-generation",
"summarization",
"en",
"arxiv:1912.08777",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | summarization | 2022-03-02T23:29:05Z | ### Pegasus Models
See Docs: [here](https://huggingface.co/transformers/master/model_doc/pegasus.html)
Original TF 1 code [here](https://github.com/google-research/pegasus)
Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019
Maintained by: [@sshleifer](https://twitter.com/sam_shleifer)... | [] |
mradermacher/Altair-Stock-12B-v1-MPOA-GGUF | mradermacher | 2026-03-07T17:21:56Z | 739 | 1 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"model_stock",
"en",
"base_model:Naphula/Altair-Stock-12B-v1-MPOA",
"base_model:quantized:Naphula/Altair-Stock-12B-v1-MPOA",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2026-03-07T15:53:38Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [
{
"start": 521,
"end": 550,
"text": "Altair-Stock-12B-v1-MPOA-GGUF",
"label": "benchmark name",
"score": 0.6159729361534119
}
] |
mradermacher/LFM2-2.6B-Uncensored-X64-GGUF | mradermacher | 2025-10-01T14:34:09Z | 131 | 3 | transformers | [
"transformers",
"gguf",
"en",
"base_model:sirev/LFM2-2.6B-Uncensored-X64",
"base_model:quantized:sirev/LFM2-2.6B-Uncensored-X64",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-01T14:17:24Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [
{
"start": 519,
"end": 548,
"text": "LFM2-2.6B-Uncensored-X64-GGUF",
"label": "benchmark name",
"score": 0.6446950435638428
}
] |
tvall43/Qwen3.5-14B-A3B-Claude-4.6-Opus-Reasoning-Distilled-reap | tvall43 | 2026-03-09T17:46:49Z | 217 | 2 | transformers | [
"transformers",
"safetensors",
"qwen3_5_moe_text",
"image-text-to-text",
"text-generation-inference",
"unsloth",
"qwen3_5_moe",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"text-generation",
"conversational",
"zh",
"en",
"ko",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtere... | text-generation | 2026-03-09T17:34:21Z | # more crazy reap
can i fit moe qwen3.5 in 10gb vram? since thats already risky, lets yolo and use claude distil too. 0.65 compression this time. my original goal was 8gb vram but i mathed wrong somewhere. that fits fine on my gpro x080 but not single gpu in the radeon v340l. maybe ill give it another attempt if it tur... | [] |
zerofata/G4-MeroMero-26B-A4B | zerofata | 2026-05-02T03:51:29Z | 125 | 52 | null | [
"safetensors",
"gemma4",
"dataset:zerofata/Instruct-Anime",
"dataset:zerofata/Gemini-3.1-Pro-SmallWiki",
"dataset:zerofata/Gemini-3.1-Pro-GLM5-Characters",
"dataset:zerofata/Roleplay-Anime-Characters",
"base_model:google/gemma-4-26B-A4B-it",
"base_model:finetune:google/gemma-4-26B-A4B-it",
"license:... | null | 2026-04-15T21:32:02Z | <style>
.gs {
--bg: #0d0a10;
--surface: #14101a;
--edge: #2a1f38;
--rule: #382850;
--text: #b8a0cc;
--dim: #7a6090;
--bright: #f0e6ff;
--azure: #c060ff;
--crimson: #ff4da6;
--az-glow: rgba(192,96,255,0.10);
--cr-glow: rgba(255,77,166,0.06);
--mono: 'JetBrains Mono', monos... | [] |
BAAI/bge-base-en-v1.5 | BAAI | 2024-02-21T03:00:19Z | 5,277,894 | 407 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"mteb",
"en",
"arxiv:2401.03462",
"arxiv:2312.15503",
"arxiv:2311.13534",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"model-index",
"text-embe... | feature-extraction | 2023-09-11T15:04:22Z | <h1 align="center">FlagEmbedding</h1>
<h4 align="center">
<p>
<a href=#model-list>Model List</a> |
<a href=#frequently-asked-questions>FAQ</a> |
<a href=#usage>Usage</a> |
<a href="#evaluation">Evaluation</a> |
<a href="#train">Train</a> |
<a href="#contact">Conta... | [] |
facebook/nllb-200-1.3B | facebook | 2023-02-11T20:19:16Z | 30,943 | 71 | transformers | [
"transformers",
"pytorch",
"m2m_100",
"text2text-generation",
"nllb",
"translation",
"ace",
"acm",
"acq",
"aeb",
"af",
"ajp",
"ak",
"als",
"am",
"apc",
"ar",
"ars",
"ary",
"arz",
"as",
"ast",
"awa",
"ayr",
"azb",
"azj",
"ba",
"bm",
"ban",
"be",
"bem",
"b... | translation | 2022-07-08T10:42:11Z | # NLLB-200
This is the model card of NLLB-200's 1.3B variant.
Here are the [metrics](https://tinyurl.com/nllb200dense1bmetrics) for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and t... | [
{
"start": 1842,
"end": 1856,
"text": "chrF++ metrics",
"label": "evaluation metric",
"score": 0.7162339091300964
}
] |
unsloth/ERNIE-4.5-21B-A3B-Thinking-GGUF | unsloth | 2026-01-24T07:38:41Z | 2,432 | 52 | transformers | [
"transformers",
"gguf",
"ERNIE4.5",
"text-generation",
"en",
"zh",
"base_model:baidu/ERNIE-4.5-21B-A3B-Thinking",
"base_model:quantized:baidu/ERNIE-4.5-21B-A3B-Thinking",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-09-10T11:01:33Z | <div align="center" style="line-height: 1;">
<a href="https://ernie.baidu.com/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/🤖_Chat-ERNIE_Bot-blue" style="display: inline-block; vertical-align: middle;"/>
</a>
<a href="https://huggingface.co/baidu" target="_blank" s... | [] |
IDEA-Research/Rex-Thinker-GRPO-7B | IDEA-Research | 2025-06-09T12:32:51Z | 130 | 9 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"zero-shot-object-detection",
"en",
"arxiv:2506.04034",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | zero-shot-object-detection | 2025-05-23T04:01:02Z | <div align=center>
<img src="assets/logo.png" width=300 >
</div>
# 🦖🧠 Rex-Thinker: Grounded Object Refering via Chain-of-Thought Reasoning 🦖🧠
<div align=center>
<p align="center">
<a href="https://bagel-ai.org/">
<img
src="https://img.shields.io/badge/RexThinker-Website-Red?logo=afdian&logoColor=wh... | [] |
unsloth/medgemma-4b-it-GGUF | unsloth | 2025-07-15T09:43:01Z | 18,033 | 65 | transformers | [
"transformers",
"gguf",
"gemma3",
"image-text-to-text",
"medical",
"unsloth",
"radiology",
"clinical-reasoning",
"dermatology",
"pathology",
"ophthalmology",
"chest-x-ray",
"arxiv:2303.15343",
"arxiv:2507.05201",
"arxiv:2405.03162",
"arxiv:2106.14463",
"arxiv:2412.03555",
"arxiv:25... | image-text-to-text | 2025-05-20T19:18:08Z | <div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
<div style="display: flex; gap: 5px; align-items: center; ">
<a href="https://github.com/u... | [] |
saricles/MiniMax-M2.7-NVFP4-GB10 | saricles | 2026-04-19T14:34:54Z | 1,684 | 6 | transformers | [
"transformers",
"safetensors",
"minimax_m2",
"text-generation",
"minimax",
"nvfp4",
"4-bit",
"quantized",
"compressed-tensors",
"vllm",
"DGX-Spark",
"GB10",
"MoE",
"conversational",
"custom_code",
"en",
"zh",
"base_model:MiniMaxAI/MiniMax-M2.7",
"base_model:finetune:MiniMaxAI/Min... | text-generation | 2026-04-15T04:11:57Z | # MiniMax-M2.7-NVFP4-GB10
Custom GB10 NVFP4 quantization of [MiniMaxAI/MiniMax-M2.7](https://huggingface.co/MiniMaxAI/MiniMax-M2.7) (230B, 256 MoE experts, top-K=8) targeted at NVIDIA DGX Spark (GB10) and Blackwell-family hardware. 130.6 GB on disk, down from the 230.2 GB official FP8 release.
## Model Details
| | |... | [] |
Tesslate/OmniCoder-9B | Tesslate | 2026-03-13T03:17:34Z | 21,202 | 417 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"qwen3.5",
"code",
"agent",
"sft",
"omnicoder",
"tesslate",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen3.5-9B",
"base_model:finetune:Qwen/Qwen3.5-9B",
"license:apache-2.0",
"model-index",
"endpoint... | text-generation | 2026-03-12T06:56:44Z | <div align="center">
<img src="omnicoder-banner.png" alt="OmniCoder" width="720">
# OmniCoder-9B
### A 9B coding agent fine-tuned on 425K agentic trajectories.
[](https://opensource.org/licenses/Apache-2.0)
[![Base Model](https://img.shields.io/bad... | [] |
nvidia/Llama-3.1-Nemotron-Safety-Guard-8B-v3 | nvidia | 2025-10-28T18:28:23Z | 1,670 | 14 | null | [
"safetensors",
"llama",
"content moderation",
"llm safety",
"multilingual content safety",
"multilingual guard model",
"toxicity detection",
"CultureGuard",
"Nemotron",
"text-generation",
"conversational",
"en",
"ar",
"de",
"es",
"fr",
"hi",
"ja",
"th",
"zh",
"dataset:nvidia/... | text-generation | 2025-08-20T10:17:55Z | # Llama-3.1-Nemotron-Safety-Guard-8B-v3
## Model Overview
**Llama-3.1-Nemotron-Safety-Guard-8B-v3** is a multilingual content safety model that moderates human-LLM interaction content and classifies user prompts and LLM responses as safe or unsafe. If the content is unsafe, the model additionally returns a response ... | [] |
mit-han-lab/dc-ae-f32c32-sana-1.0-diffusers | mit-han-lab | 2025-01-06T14:55:50Z | 301 | 16 | diffusers | [
"diffusers",
"safetensors",
"arxiv:2410.10733",
"region:us"
] | null | 2024-12-05T11:34:09Z | # Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models
[[paper](https://arxiv.org/abs/2410.10733)] [[GitHub](https://github.com/mit-han-lab/efficientvit)]
<p align="center">
<b> Figure 1: We address the reconstruction accuracy drop of high spatial-compression auto... | [] |
zerofata/GLM-4.5-Iceblink-v3-106B-A12B-GGUF | zerofata | 2026-03-12T08:46:44Z | 1,089 | 2 | null | [
"gguf",
"base_model:zerofata/GLM-4.5-Iceblink-v3-106B-A12B",
"base_model:quantized:zerofata/GLM-4.5-Iceblink-v3-106B-A12B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-11T00:42:47Z | <style>
.ib {
--bg: #e4eef6;
--panel: rgba(255,255,255,0.7);
--accent: #4a9ec8;
--accent2: #78c4e0;
--accent3: #a0d8ef;
--border: #b0cedf;
--text: #1e3040;
--muted: #5a7a90;
--bright: #2884b0;
--white: #ffffff;
--crystal: rgba(74,158,200,0.12);
--mono: 'JetBrains Mono', monos... | [] |
OuteAI/OuteTTS-0.2-500M-GGUF | OuteAI | 2024-12-03T08:11:40Z | 5,031 | 83 | null | [
"gguf",
"text-to-speech",
"en",
"zh",
"ja",
"ko",
"dataset:facebook/multilingual_librispeech",
"dataset:parler-tts/libritts_r_filtered",
"dataset:amphion/Emilia-Dataset",
"dataset:parler-tts/mls_eng",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | text-to-speech | 2024-11-24T08:06:46Z | <style>
table {
border-collapse: collapse;
width: 100%;
margin-bottom: 20px;
}
th, td {
border: 1px solid #ddd;
padding: 8px;
text-align: center;
}
.best {
font-weight: bold;
text-decoration: underline;
}
.box {
text-align: center;
margin: 20px auto;
padding: 30px;
box-shadow: 0p... | [] |
woraamy/ByStander-7B-Thai | woraamy | 2026-02-17T13:38:22Z | 105 | 1 | null | [
"gguf",
"qwen2",
"openthaigpt",
"qwen",
"emergency-response",
"first-aid",
"medical-guidance",
"bystander",
"text-generation",
"conversational",
"th",
"en",
"base_model:openthaigpt/openthaigpt1.5-7b-instruct",
"base_model:quantized:openthaigpt/openthaigpt1.5-7b-instruct",
"license:other"... | text-generation | 2026-02-17T02:59:06Z | # 🇹🇭 ByStander-7B-Thai
**ByStander-7B-Thai** is a specialized Thai Large Language Model (LLM) fine-tuned for **Emergency Situation Guidance**. It is built on top of **OpenThaiGPT 1.5 (7B)** and is designed to assist users during critical moments by providing life-saving instructions, identifying emergency severity, ... | [] |
perplexity-ai/pplx-embed-context-v1-4b | perplexity-ai | 2026-03-02T09:28:59Z | 19,352 | 31 | transformers | [
"transformers",
"onnx",
"safetensors",
"bidirectional_pplx_qwen3",
"feature-extraction",
"sentence-similarity",
"conteb",
"contextual-embeddings",
"custom_code",
"multilingual",
"arxiv:2602.11151",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2026-01-20T13:45:35Z | <p align="center">
<img src="assets/logo.svg" alt="Perplexity Logo" width="400">
</p>
<p align="center">pplx-embed-v1: Diffusion-Pretrained Dense and Contextual Embeddings</p>
`pplx-embed-v1` and `pplx-embed-context-v1` are state-of-the-art text embedding models optimized for real-world, web-scale retrieval tasks.
... | [] |
mradermacher/Huihui-HY-MT1.5-7B-abliterated-GGUF | mradermacher | 2026-01-05T09:37:12Z | 514 | 2 | transformers | [
"transformers",
"gguf",
"translation",
"abliterated",
"uncensored",
"zh",
"en",
"fr",
"pt",
"es",
"ja",
"tr",
"ru",
"ar",
"ko",
"th",
"it",
"de",
"vi",
"ms",
"id",
"tl",
"hi",
"pl",
"cs",
"nl",
"km",
"my",
"fa",
"gu",
"ur",
"te",
"mr",
"he",
"bn",
... | translation | 2026-01-05T07:13:21Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
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