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 |
|---|---|---|---|---|---|---|---|---|---|---|
Bedovyy/LTX2.3_transformer_only_comfy | Bedovyy | 2026-03-18T05:13:23Z | 604 | 7 | diffusion-single-file | [
"diffusion-single-file",
"comfyui",
"base_model:Lightricks/LTX-2.3",
"base_model:quantized:Lightricks/LTX-2.3",
"license:other",
"region:us"
] | null | 2026-03-17T15:04:04Z | # transformer_only models of LTX-2.3 (experimental)
- You can get rest of model from [Kijai/LTX2.3_comfy](https://huggingface.co/Kijai/LTX2.3_comfy).
- You may need to fetch [pr-12978](https://github.com/Comfy-Org/ComfyUI/pull/12978) on ComfyUI for Lora.
- nvfp4 and mxfp8 are fast only on the RTX 5000 series.
## Upda... | [] |
cyankiwi/Qwen3-4B-Instruct-2507-AWQ-8bit | cyankiwi | 2025-08-08T04:52:03Z | 1,582 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"arxiv:2505.09388",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:quantized:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"compressed-tensors",
"reg... | text-generation | 2025-08-08T04:46:11Z | # Qwen3-4B-Instruct-2507
<a href="https://chat.qwen.ai" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Highlights
We introduce the updated version of the **Qwen3... | [
{
"start": 2,
"end": 24,
"text": "Qwen3-4B-Instruct-2507",
"label": "benchmark name",
"score": 0.7906982898712158
},
{
"start": 315,
"end": 323,
"text": "Qwen3-4B",
"label": "benchmark name",
"score": 0.643234372138977
},
{
"start": 353,
"end": 375,
"text"... |
mradermacher/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT-GGUF | mradermacher | 2026-03-30T00:21:00Z | 588 | 1 | transformers | [
"transformers",
"gguf",
"merlina",
"grimoire",
"text-generation",
"sft",
"en",
"dataset:hemlang/Hemlock-SFT",
"base_model:nbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT",
"base_model:quantized:nbeerbower/Huihui-Qwen3.5-9B-abliterated-TIES-Hemlock-SFT",
"endpoints_compatible",
"regio... | text-generation | 2026-03-29T13:56:14Z | ## 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: 1 -->
static ... | [] |
KRLabsOrg/squeez-2b | KRLabsOrg | 2026-04-27T13:39:55Z | 865 | 2 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"code",
"tool-output",
"pruning",
"coding-agents",
"extraction",
"text-generation",
"conversational",
"en",
"dataset:KRLabsOrg/tool-output-extraction-swebench",
"arxiv:2604.04979",
"base_model:Qwen/Qwen3.5-2B",
"base_model... | text-generation | 2026-03-16T08:26:18Z | <p align="center">
<img src="https://raw.githubusercontent.com/KRLabsOrg/squeez/main/assets/squeez_mascot.png" alt="Squeez mascot" width="180">
</p>
# Squeez-2B
**Squeez-2B** is a 2B parameter model fine-tuned from Qwen 3.5 2B for task-conditioned tool-output pruning in coding agents. Given a focused query and one ... | [
{
"start": 118,
"end": 124,
"text": "Squeez",
"label": "benchmark name",
"score": 0.6839079260826111
},
{
"start": 154,
"end": 163,
"text": "Squeez-2B",
"label": "benchmark name",
"score": 0.6525776386260986
},
{
"start": 167,
"end": 176,
"text": "Squeez-2... |
unsloth/grok-2-GGUF | unsloth | 2025-09-08T21:43:57Z | 2,543 | 56 | transformers | [
"transformers",
"gguf",
"grok",
"unsloth",
"base_model:xai-org/grok-2",
"base_model:quantized:xai-org/grok-2",
"license:other",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-09-06T08:10:21Z | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>Learn how to run Grok 2 correctly - <a href="https://docs.unsloth.ai/basics/grok-2">Read our Guide</a>.</strong>
</p>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic ... | [] |
Vaultkeeper/ouroboros-next | Vaultkeeper | 2026-03-11T14:49:25Z | 2,431 | 6 | transformers | [
"transformers",
"gguf",
"qwen3_5",
"image-text-to-text",
"text-generation",
"mergekit",
"coding",
"agentic",
"reasoning",
"vision",
"qwen3.5",
"phi-4",
"merge",
"mixture-of-experts",
"ouroboros",
"conversational",
"en",
"base_model:crownelius/Crow-9B-Opus-4.6-Distill-Heretic_Qwen3.... | text-generation | 2026-03-09T18:48:24Z | <div align="center" style="display: flex; justify-content: center; align-items: center; gap: 40px; flex-wrap: wrap; margin: 2em 0;">
<img src="https://huggingface.co/Vaultkeeper/ouroboros-next/resolve/main/ouroboros-next-logo.png" alt="Ouroboros-Next" width="400" style="max-height: 400px;" />
<div style="text-al... | [] |
cyankiwi/GLM-4.7-Flash-REAP-23B-A3B-AWQ-4bit | cyankiwi | 2026-01-25T21:01:31Z | 9,502 | 2 | transformers | [
"transformers",
"safetensors",
"glm4_moe_lite",
"text-generation",
"glm",
"MOE",
"pruning",
"compression",
"conversational",
"en",
"arxiv:2510.13999",
"base_model:cerebras/GLM-4.7-Flash-REAP-23B-A3B",
"base_model:quantized:cerebras/GLM-4.7-Flash-REAP-23B-A3B",
"license:mit",
"endpoints_c... | text-generation | 2026-01-25T17:35:33Z | <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>
# GLM-4.7-Flash-REAP-23B-A3B
## ✨ Highlights
Introducing **GLM-4.7-Flash-REAP-23B-A3B**, a **memory-efficient compress... | [] |
cyankiwi/Qwen3-VL-8B-Instruct-AWQ-4bit | cyankiwi | 2025-10-14T21:59:35Z | 85,522 | 13 | null | [
"safetensors",
"qwen3_vl",
"image-text-to-text",
"conversational",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen3-VL-8B-Instruct",
"base_model:quantized:Qwen/Qwen3-VL-8B-Instruct",
"license:apache-2.0",
"compressed-tensors",
"region:us"... | image-text-to-text | 2025-10-14T21:52:54Z | <a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
# Qwen3-VL-8B-Instruct
Meet Qwen3-VL — the most powerful vision-language model in... | [] |
elyza/ELYZA-Shortcut-1.0-Qwen-7B | elyza | 2025-04-30T15:22:09Z | 1,060 | 2 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"ja",
"en",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-30T15:19:39Z | # ELYZA-Shortcut-1.0-Qwen-7B
## Model Description
**ELYZA-Shortcut-1.0-Qwen-7B** is a non-reasoning model derived during the development of the reasoning model [ELYZA-Thinking-1.0-Qwen-32B](https://huggingface.co/elyza/ELYZA-Thinking-1.0-Qwen-32B). Based on [Qwen... | [] |
deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct | deepseek-ai | 2024-07-03T05:16:11Z | 289,102 | 566 | transformers | [
"transformers",
"safetensors",
"deepseek_v2",
"text-generation",
"conversational",
"custom_code",
"arxiv:2401.06066",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-06-14T06:23:33Z | <!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-V2" />
</div>
<hr>
<div align="center" style="line-... | [] |
datalyes/patembed-large | datalyes | 2025-10-28T12:32:50Z | 609 | 1 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"patent",
"embeddings",
"mteb",
"en",
"arxiv:2510.22264",
"license:cc-by-nc-sa-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | sentence-similarity | 2025-10-28T12:28:01Z | # patembed-large
This is a **sentence-transformers** model trained specifically for **patent text embeddings**. It is part of the **PatenTEB** project, which provides state-of-the-art models for patent document understanding and retrieval.
**Note:** This model uses task-specific instruction prompts during inference f... | [
{
"start": 133,
"end": 141,
"text": "PatenTEB",
"label": "benchmark name",
"score": 0.7883719801902771
},
{
"start": 924,
"end": 932,
"text": "PatenTEB",
"label": "benchmark name",
"score": 0.8889979720115662
},
{
"start": 1246,
"end": 1260,
"text": "patem... |
typhoon-ai/typhoon-ocr1.5-3b-qat | typhoon-ai | 2025-11-14T03:30:19Z | 105 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"OCR",
"vision-language",
"document-understanding",
"multilingual",
"QAT",
"conversational",
"en",
"th",
"arxiv:2412.13702",
"arxiv:2511.04479",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible... | image-text-to-text | 2025-11-10T05:16:02Z | # Typhoon-OCR-1.5-3B-QAT
A quantization-aware trained (QAT) version of [**Typhoon OCR v1.5**](https://huggingface.co/scb10x/typhoon-ocr1.5-2b), designed for robust and efficient on-device vision-language OCR in English and Thai.
This release maintains strong accuracy while significantly improving performance when r... | [] |
jhu-clsp/ettin-encoder-68m | jhu-clsp | 2025-07-18T14:09:39Z | 1,279 | 5 | transformers | [
"transformers",
"pytorch",
"modernbert",
"fill-mask",
"en",
"arxiv:2507.11412",
"license:mit",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-03-24T09:39:04Z | # Ettin: an Open Suite of Paired Encoders and Decoders
[](https://opensource.org/licenses/MIT)
[](https://arxiv.org/abs/2507.11412)
[![Models](https://img.shields.io/badge/🤗%20Hugging%20Face-12%20... | [] |
ServiceNow-AI/Apriel-1.5-15b-Thinker | ServiceNow-AI | 2025-10-06T18:55:51Z | 303 | 467 | transformers | [
"transformers",
"safetensors",
"llava",
"image-text-to-text",
"conversational",
"arxiv:2510.01141",
"license:mit",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-09-24T00:40:54Z | # Apriel-1.5-15b-Thinker - Mid training is all you need!
<img src="https://cdn-uploads.huggingface.co/production/uploads/63d3095c2727d7888cbb54e2/Lt1t0tOO5emz1X23Azg-E.png" width="120" alt="thumbnail"/> `/ˈɑː.pri.əl/`
---
# Table of Contents
1. [Summary](#summary)
2. [Evaluation](#evaluation)
3. [Training ... | [
{
"start": 1533,
"end": 1558,
"text": "Artificial Analysis index",
"label": "evaluation metric",
"score": 0.866405189037323
},
{
"start": 1583,
"end": 1599,
"text": "Deepseek R1 0528",
"label": "benchmark name",
"score": 0.6955155730247498
}
] |
OpenMOSS-Team/MOSS-SoundEffect | OpenMOSS-Team | 2026-03-13T09:19:24Z | 5,956 | 44 | null | [
"safetensors",
"moss_tts_delay",
"text-to-audio",
"custom_code",
"license:apache-2.0",
"region:us"
] | text-to-audio | 2026-02-08T17:44:45Z | # MOSS-TTS Family
<br>
<p align="center">
<img src="https://speech-demo.oss-cn-shanghai.aliyuncs.com/moss_tts_demo/tts_readme_imgaes_demo/openmoss_x_mosi" height="50" align="middle" />
</p>
<div align="center">
<a href="https://github.com/OpenMOSS/MOSS-TTS/tree/main"><img... | [] |
microsoft/Phi-mini-MoE-instruct | microsoft | 2025-12-10T18:20:28Z | 98,117 | 31 | transformers | [
"transformers",
"safetensors",
"phimoe",
"text-generation",
"conversational",
"custom_code",
"en",
"arxiv:2506.18349",
"arxiv:2404.14219",
"arxiv:2409.12136",
"license:mit",
"region:us"
] | text-generation | 2025-06-23T00:18:08Z | ## Model Summary
Phi-mini-MoE is a lightweight Mixture of Experts (MoE) model with 7.6B total parameters and 2.4B activated parameters. It is compressed and distilled from the base model shared by [Phi-3.5-MoE](https://huggingface.co/microsoft/Phi-3.5-MoE-instruct) and [GRIN-MoE](https://huggingface.co/microsoft/GRIN-... | [] |
datalab-to/chandra-ocr-2 | datalab-to | 2026-03-18T18:21:07Z | 11,325 | 100 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"ocr",
"pdf",
"markdown",
"layout",
"conversational",
"license:openrail",
"eval-results",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-03-16T20:47:07Z | <p align="center">
<img src="datalab-logo.png" alt="Datalab Logo" width="150"/>
</p>
# Chandra OCR 2
Chandra 2 is a state of the art OCR model from [Datalab](https://www.datalab.to) that outputs markdown, HTML, and JSON. It is highly accurate at extracting text from images and PDFs, while preserving layout informat... | [
{
"start": 516,
"end": 534,
"text": "olmocr bench score",
"label": "evaluation metric",
"score": 0.7372372150421143
},
{
"start": 549,
"end": 573,
"text": "multilingual bench score",
"label": "evaluation metric",
"score": 0.7942737936973572
}
] |
nvidia/bigvgan_v2_24khz_100band_256x | nvidia | 2024-09-05T03:36:11Z | 10,193 | 20 | PyTorch | [
"PyTorch",
"neural-vocoder",
"audio-generation",
"audio-to-audio",
"arxiv:2206.04658",
"license:mit",
"region:us"
] | audio-to-audio | 2024-07-15T11:09:36Z | ## BigVGAN: A Universal Neural Vocoder with Large-Scale Training
#### Sang-gil Lee, Wei Ping, Boris Ginsburg, Bryan Catanzaro, Sungroh Yoon
[[Paper]](https://arxiv.org/abs/2206.04658) - [[Code]](https://github.com/NVIDIA/BigVGAN) - [[Showcase]](https://bigvgan-demo.github.io/) - [[Project Page]](https://research.nvid... | [] |
cudabenchmarktest/qwen3.5-9b-qwen3.6-reasoning-distilled-GGUF | cudabenchmarktest | 2026-04-15T04:07:52Z | 4,695 | 1 | null | [
"gguf",
"qwen3.5",
"reasoning",
"distillation",
"lora",
"sft",
"text-generation",
"dataset:Crownelius/Opus-4.6-Reasoning-3300x",
"base_model:Qwen/Qwen3.5-9B",
"base_model:adapter:Qwen/Qwen3.5-9B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-04-09T03:03:45Z | > ## ⚠️ CRITICAL: Ollama Inference Flag Required
>
> **If you serve this model via Ollama with the qwen3.5 RENDERER (the standard
> recommended setup), you MUST pass `"think": false` in the `/api/chat`
> request body for chat / instruction following / tool use.**
>
> ```bash
> curl -X POST http://localhost:11434/api/ch... | [] |
cyankiwi/gemma-4-26B-A4B-it-AWQ-4bit | cyankiwi | 2026-05-01T21:56:38Z | 1,241,429 | 57 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"conversational",
"base_model:google/gemma-4-26B-A4B-it",
"base_model:quantized:google/gemma-4-26B-A4B-it",
"license:apache-2.0",
"endpoints_compatible",
"compressed-tensors",
"region:us"
] | image-text-to-text | 2026-04-03T00:28:19Z | <div align="center">
<img src="https://huggingface.co/buckets/cyankiwi/activation-aware-2.0/resolve/banner/cyankiwi-banner-awq-0.png">
</div>
<div align="left">
<table align="center" style="border-collapse:collapse; border:none;">
<tr style="border:none;">
<td align="right" style="border:none; padding:4p... | [] |
second-state/StarCoder2-15B-GGUF | second-state | 2024-03-20T08:11:55Z | 2,222 | 32 | transformers | [
"transformers",
"gguf",
"starcoder2",
"text-generation",
"code",
"base_model:bigcode/starcoder2-15b",
"base_model:quantized:bigcode/starcoder2-15b",
"license:bigcode-openrail-m",
"region:us"
] | text-generation | 2024-03-02T03:32:13Z | <!-- 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 ... | [] |
baichuan-inc/Baichuan-M3-235B-GPTQ-INT4 | baichuan-inc | 2026-02-09T03:45:45Z | 373 | 10 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"chat",
"conversational",
"en",
"zh",
"arxiv:2602.06570",
"base_model:Qwen/Qwen3-235B-A22B",
"base_model:quantized:Qwen/Qwen3-235B-A22B",
"license:apache-2.0",
"endpoints_compatible",
"4-bit",
"gptq",
"region:us"
] | text-generation | 2026-01-13T02:18:45Z | <div align="center">
# Baichuan-M3-235B-GPTQ-INT4
[](https://opensource.org/licenses/Apache-2.0)
[](https://huggingface.co/baichuan-inc/Baichuan-M3-235B)
[![M3 FP8](https... | [] |
grammarly/coedit-large | grammarly | 2024-04-28T02:30:16Z | 140,098 | 155 | transformers | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"en",
"dataset:facebook/asset",
"dataset:wi_locness",
"dataset:GEM/wiki_auto_asset_turk",
"dataset:discofuse",
"dataset:zaemyung/IteraTeR_plus",
"dataset:jfleg",
"dataset:grammarly/coedit",
"arxiv:2305.09857",
"licen... | null | 2023-05-11T23:57:35Z | # Model Card for CoEdIT-Large
This model was obtained by fine-tuning the corresponding `google/flan-t5-large` model on the CoEdIT dataset. Details of the dataset can be found in our paper and repository.
**Paper:** CoEdIT: Text Editing by Task-Specific Instruction Tuning
**Authors:** Vipul Raheja, Dhruv Kumar, Ryan ... | [] |
UnstableLlama/Qwen3.5-27B-exl3 | UnstableLlama | 2026-03-31T07:10:12Z | 681 | 13 | null | [
"qwen3_5",
"exl3",
"base_model:Qwen/Qwen3.5-27B",
"base_model:quantized:Qwen/Qwen3.5-27B",
"license:apache-2.0",
"8-bit",
"region:us"
] | null | 2026-03-03T13:45:07Z | <style>
@import url('https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;700&family=Inter:wght@400;700&display=swap');
.dashboard-container {
font-family: 'Inter', sans-serif;
width: min(1500px, calc(100vw - 32px));
max-width: 100%;
margin: 0 auto;
box-sizing: border-box;
backg... | [] |
Qwen/Qwen3-ForcedAligner-0.6B | Qwen | 2026-01-30T03:00:55Z | 167,653 | 102 | null | [
"safetensors",
"qwen3_asr",
"automatic-speech-recognition",
"arxiv:2601.21337",
"license:apache-2.0",
"region:us"
] | automatic-speech-recognition | 2026-01-28T03:29:54Z | # Qwen3-ASR
## Overview
### Introduction
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-ASR-Repo/qwen3_asr_introduction.png" width="90%"/>
<p>
The Qwen3-ASR family includes Qwen3-ASR-1.7B and Qwen3-ASR-0.6B, which support language identification and ASR for 52 languages and d... | [] |
lightseekorg/kimi-k2.5-eagle3-mla | lightseekorg | 2026-04-30T18:11:48Z | 42,457 | 1 | null | [
"safetensors",
"kimi_k2",
"text-generation",
"speculative-decoding",
"eagle3",
"kimi-k2.5",
"torchspec",
"base_model:moonshotai/Kimi-K2.5",
"base_model:finetune:moonshotai/Kimi-K2.5",
"license:other",
"region:us"
] | text-generation | 2026-04-06T02:27:42Z | # kimi-k2.5-eagle3-mla
## Model Overview
kimi-k2.5-eagle3-mla is an Eagle3 MTP draft model with MLA(Multi-Latent-Attention) for accelerating inference of [Kimi-K2.5](https://huggingface.co/moonshotai/Kimi-K2.5), trained with [TorchSpec](https://github.com/torchspec-project/TorchSpec) - an online speculative decoding ... | [
{
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"text": "kimi-k2.5-eagle3-mla",
"label": "benchmark name",
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},
{
"start": 157,
"end": 166,
"text": "Kimi-K2.5",
"label": "benchmark name",
"score": 0.8586707711219788
},
{
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"end": 211,
"text... |
quwsarohi/NanoAgent-135M | quwsarohi | 2026-04-20T02:41:11Z | 2,362 | 24 | mlx | [
"mlx",
"safetensors",
"llama",
"llm",
"tool-calling",
"lightweight",
"agentic-tasks",
"react",
"text-generation",
"conversational",
"en",
"dataset:microsoft/orca-agentinstruct-1M-v1",
"dataset:microsoft/orca-math-word-problems-200k",
"dataset:allenai/tulu-3-sft-personas-instruction-followi... | text-generation | 2025-10-09T18:38:44Z | # 🧠 NanoAgent — A 135M Parameter Agentic SLM
NanoAgent is a **135M parameter**, **8k context length**, open-source language model designed for **agentic tasks** such as **tool calling**, **instruction following**, and **lightweight reasoning**.
It’s small enough (~135 MB in 8-bit) to run on **edge devices** like pe... | [] |
profpeng/doublepenetration | profpeng | 2026-01-06T23:32:27Z | 853 | 1 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:Wan-AI/Wan2.2-I2V-A14B",
"base_model:adapter:Wan-AI/Wan2.2-I2V-A14B",
"region:us"
] | text-to-image | 2026-01-06T23:32:12Z | # doublepenetration
<Gallery />
## Model description
Prompt: a woman, the camera quickly pulls back to reveal her vagina, her breasts are bouncing and her ass are bouncing, she was sitting on top of a black man, the black man beneath her thrusting his black penis in and out of her anus, another black man on the lef... | [] |
labhamlet/wavjepa-nat-base | labhamlet | 2025-11-06T15:46:21Z | 550 | 1 | transformers | [
"transformers",
"safetensors",
"wavjepa-nat-base",
"feature-extraction",
"audio",
"speech",
"waveform",
"custom_code",
"dataset:agkphysics/AudioSet",
"arxiv:2509.23238",
"license:mit",
"region:us"
] | feature-extraction | 2025-11-04T16:46:07Z | # Model Card for Model ID
WavJEPANat, a waveform-based version of the Joint-Embedding Predictive Architecture. WavJEPANat leverages high-level semantic representation learning to tackle the shortcomings of representation learning at the speech unit or token level. We show that
this approach substantially outperforms s... | [
{
"start": 1451,
"end": 1455,
"text": "HEAR",
"label": "benchmark name",
"score": 0.6859880089759827
},
{
"start": 2221,
"end": 2225,
"text": "HEAR",
"label": "benchmark name",
"score": 0.7705212831497192
}
] |
unsloth/DeepSeek-R1-GGUF | unsloth | 2025-05-30T07:44:07Z | 40,085 | 1,102 | transformers | [
"transformers",
"gguf",
"deepseek_v3",
"text-generation",
"deepseek",
"unsloth",
"custom_code",
"en",
"arxiv:2501.12948",
"base_model:deepseek-ai/DeepSeek-R1",
"base_model:quantized:deepseek-ai/DeepSeek-R1",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-01-20T13:09:42Z | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/deepseek-r1-all-versions-678e1c48f5d2fce87892ace5">our collection</a> for versions of Deepseek-R1 including GGUF & 4-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em>Unsloth's Dee... | [] |
mradermacher/aligner2-7b-GGUF | mradermacher | 2025-11-26T05:55:43Z | 523 | 1 | transformers | [
"transformers",
"gguf",
"llama-factory",
"full",
"generated_from_trainer",
"en",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-26T05:20:52Z | ## 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... | [] |
openbmb/NOSA-8B | openbmb | 2026-02-12T07:36:38Z | 4,957 | 10 | transformers | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
"custom_code",
"en",
"zh",
"dataset:openbmb/InfLLM-V2-data-5B",
"arxiv:2510.13602",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-04T07:51:57Z | <div align="center">
<h1>NOSA: Native and Offloadable Sparse Attention</h1>
**Boost Decoding Efficiency via High-Locality Offloading**
</div>
<div align="center" style="line-height: 1;">
<a href="https://github.com/thunlp/NOSA" style="margin: 2px;">
<img alt="Code" src="https://img.shields.io/badge/GitHub-100... | [] |
baa-ai/Gemma-4-26B-A4B-it-RAM-20GB-MLX | baa-ai | 2026-04-15T13:17:28Z | 1,722 | 4 | mlx | [
"mlx",
"safetensors",
"gemma4",
"quantized",
"mixed-precision",
"moe",
"base_model:google/gemma-4-26B-A4B-it",
"base_model:quantized:google/gemma-4-26B-A4B-it",
"license:other",
"4-bit",
"region:us"
] | null | 2026-04-06T13:15:04Z | # Gemma-4-26B-A4B-it — 20GB (MLX)
Mixed-precision quantized version of [google/gemma-4-26B-A4B-it](https://huggingface.co/google/gemma-4-26B-A4B-it) 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-constra... | [
{
"start": 2,
"end": 20,
"text": "Gemma-4-26B-A4B-it",
"label": "benchmark name",
"score": 0.7369486093521118
},
{
"start": 828,
"end": 836,
"text": "Shepherd",
"label": "benchmark name",
"score": 0.6164291501045227
},
{
"start": 1378,
"end": 1386,
"text":... |
mradermacher/LFM2.5-1.2B-Thinking-Gemini-Pro-Heretic-Uncensored-DISTILL-GGUF | mradermacher | 2026-02-16T17:10:59Z | 177 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"finetune",
"heretic",
"uncensored",
"abliterated",
"All use cases",
"bfloat16",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
... | null | 2026-02-16T17:04:02Z | ## 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": 555,
"end": 618,
"text": "LFM2.5-1.2B-Thinking-Gemini-Pro-Heretic-Uncensored-DISTILL-GGUF",
"label": "benchmark name",
"score": 0.6698518395423889
}
] |
kuleshov-group/mdlm-owt | kuleshov-group | 2026-04-11T21:42:32Z | 37,964 | 22 | transformers | [
"transformers",
"safetensors",
"mdlm",
"fill-mask",
"custom_code",
"en",
"dataset:Skylion007/openwebtext",
"arxiv:2406.07524",
"license:apache-2.0",
"region:us"
] | fill-mask | 2024-06-06T18:47:47Z | ## Using MDLM
To use the pre-trained model for masked language modeling, use the following snippet:
```python
from transformers import AutoModelForMaskedLM, AutoTokenizer
# See the `MDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('gpt2')
model_name ... | [] |
SulphurAI/Sulphur-2-base | SulphurAI | 2026-05-04T06:18:16Z | 20,187 | 150 | diffusers | [
"diffusers",
"gguf",
"text-to-video",
"endpoints_compatible",
"region:us",
"conversational"
] | text-to-video | 2026-05-03T00:33:24Z | **Sulphur 2**
An uncensored video generation model based on LTX 2.3 supporting both t2v and i2v natively, as well as all of the other ltx 2.3 formats.
Join our **[Discord](https://discord.gg/GSXJhKZ9V)**
---
**Get Started:**
To get started with the model, I recommend downloading either of the dev versions, (fp8mix... | [] |
Salesforce/moirai-2.0-R-small | Salesforce | 2026-01-29T02:01:22Z | 477,933 | 37 | null | [
"safetensors",
"time series",
"forecasting",
"pretrained models",
"foundation models",
"time series foundation models",
"time-series",
"time-series-forecasting",
"arxiv:2403.07815",
"arxiv:2402.02592",
"arxiv:2511.11698",
"license:cc-by-nc-4.0",
"region:us"
] | time-series-forecasting | 2025-08-06T14:03:58Z | # Moirai-2.0-R-Small
Moirai 2.0 is a decoder-only universal time series forecasting transformer model pre-trained on:
- Subset of [GIFT-Eval Pretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) datasets (Non-leaking historical context)... | [] |
nvidia/MM-Embed | nvidia | 2024-11-06T20:59:16Z | 426 | 66 | null | [
"safetensors",
"llava_next",
"custom_code",
"en",
"arxiv:2210.07316",
"arxiv:2405.17428",
"arxiv:2411.02571",
"license:cc-by-nc-4.0",
"region:us"
] | null | 2024-10-30T20:30:25Z | ## Introduction
We introduce MM-Embed, an extension of NV-Embed-v1 with multimodal retrieval capability.
MM-Embed achieves state-of-the-art results in [UniIR benchmark](https://huggingface.co/TIGER-Lab/UniIR) with 52.7 averaged score compared to 48.9 (the best results in [UnIR benchmark paper](https://eccv.ecva.net/vi... | [
{
"start": 153,
"end": 158,
"text": "UniIR",
"label": "benchmark name",
"score": 0.7961118221282959
},
{
"start": 203,
"end": 208,
"text": "UniIR",
"label": "benchmark name",
"score": 0.7123456001281738
},
{
"start": 493,
"end": 497,
"text": "MTEB",
"l... |
bgg1996/Melinoe-30B-A3B-Thinking | bgg1996 | 2025-11-08T21:11:16Z | 322 | 10 | null | [
"safetensors",
"qwen3_moe",
"en",
"base_model:Qwen/Qwen3-30B-A3B-Thinking-2507",
"base_model:finetune:Qwen/Qwen3-30B-A3B-Thinking-2507",
"license:apache-2.0",
"region:us"
] | null | 2025-11-08T05:12:04Z | # Model Card for Melinoe-30B-A3B-Thinking
## Model Description
**Melinoe-30B-A3B-Thinking** is a large language model fine-tuned for engaging in empathetic, intellectually stimulating, and deeply personal conversations. Built upon the powerful reasoning foundation of `Qwen/Qwen3-30B-A3B-Thinking`, this model is desig... | [] |
Surpem/Supertron1-4B | Surpem | 2026-04-17T11:07:31Z | 752 | 4 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"reasoning",
"math",
"coding",
"instruction-tuned",
"pytorch",
"conversational",
"en",
"base_model:Qwen/Qwen3-4B",
"base_model:finetune:Qwen/Qwen3-4B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
... | text-generation | 2026-04-13T12:52:34Z | # **Supertron1-4B: A Capable, Efficient Instruction-Tuned Language Model**
## **Model Description**
**Supertron1-4B** is an instruction-tuned language model built on top of Qwen3-4B. Designed to be a **reliable, efficient daily driver**, it delivers strong performance across math, coding, reasoning, and general conve... | [
{
"start": 4,
"end": 17,
"text": "Supertron1-4B",
"label": "benchmark name",
"score": 0.9154413938522339
},
{
"start": 104,
"end": 117,
"text": "Supertron1-4B",
"label": "benchmark name",
"score": 0.9020179510116577
},
{
"start": 551,
"end": 559,
"text": "... |
dllm-hub/Qwen2.5-Coder-0.5B-Instruct-diffusion-mdlm-v0.1 | dllm-hub | 2026-02-27T01:48:03Z | 400 | 5 | null | [
"safetensors",
"a2d-qwen2",
"custom_code",
"arxiv:2406.07524",
"arxiv:2602.22661",
"license:apache-2.0",
"region:us"
] | null | 2025-12-04T18:43:09Z | <center> <div style="text-align: center;"> <img src="https://raw.githubusercontent.com/ZHZisZZ/dllm/main/assets/logo.gif" width="400" />
</div> </center>
# Qwen2.5-Coder-0.5B-Instruct-diffusion-mdlm-v0.1
Qwen2.5-Coder-0.5B-Instruct-diffusion-mdlm-v0.1 is a diffusion-based language model adapted from [Qwen2.5-Coder-0... | [] |
mradermacher/aquif-3.5-8B-Think-GGUF | mradermacher | 2025-09-07T14:49:54Z | 115 | 2 | transformers | [
"transformers",
"gguf",
"language",
"aquif",
"text-generation-inference",
"math",
"coding",
"small",
"aquif-3.5",
"en",
"de",
"it",
"pt",
"fr",
"hi",
"es",
"th",
"zh",
"ja",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-31T08:45:14Z | ## 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... | [] |
dennisjooo/Birds-Classifier-EfficientNetB2 | dennisjooo | 2024-05-27T02:04:48Z | 5,067 | 24 | transformers | [
"transformers",
"pytorch",
"onnx",
"safetensors",
"efficientnet",
"image-classification",
"biology",
"efficientnet-b2",
"vision",
"base_model:google/efficientnet-b2",
"base_model:quantized:google/efficientnet-b2",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
... | image-classification | 2023-09-24T09:59:52Z | # Bird Classifier EfficientNet-B2
## Model Description
Have you look at a bird and said "Boahh if only I know what bird that is".
Unless you're an avid bird spotter (or just love birds in general), it's hard to differentiate some species of birds.
Well you're in luck, turns out you can use a image classifier to ide... | [] |
bartowski/TheDrummer_Anubis-Mini-8B-v1-GGUF | bartowski | 2026-03-17T17:45:27Z | 2,463 | 3 | null | [
"gguf",
"text-generation",
"base_model:TheDrummer/Anubis-Mini-8B-v1",
"base_model:quantized:TheDrummer/Anubis-Mini-8B-v1",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-03-17T17:20:02Z | ## Llamacpp imatrix Quantizations of Anubis-Mini-8B-v1 by TheDrummer
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/b8388">b8388</a> for quantization.
Original model: https://huggingface.co/TheDrummer/Anubis-Mini-8B-v1
All quan... | [] |
Sisigoks/FloraSense | Sisigoks | 2025-06-01T16:30:51Z | 224 | 1 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"biology",
"plants",
"flora",
"10K",
"en",
"dataset:Sisigoks/Planter_GARDEN_EDITION",
"base_model:google/vit-base-patch16-224",
"base_model:finetune:google/vit-base-patch16-224",
"license:mit",
"endpoints_compat... | image-classification | 2025-05-26T12:00:14Z | # 🌿 Sisigoks/FloraSense
**FloraSense** is a fine-tuned Vision Transformer (ViT) model designed for accurate classification of plant species and flora-related imagery. It builds on top of the powerful `google/vit-base-patch16-224` base model and is fine-tuned on the **Planter_GARDEN_EDITION** dataset curated by [Sisig... | [
{
"start": 826,
"end": 845,
"text": "Evaluation Accuracy",
"label": "evaluation metric",
"score": 0.8244344592094421
},
{
"start": 851,
"end": 857,
"text": "35.46%",
"label": "evaluation metric",
"score": 0.6531208753585815
}
] |
mradermacher/Magidonia-24B-v4.3-absolute-heresy-i1-GGUF | mradermacher | 2026-01-21T21:28:06Z | 1,113 | 3 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:MuXodious/Magidonia-24B-v4.3-absolute-heresy",
"base_model:quantized:MuXodious/Magidonia-24B-v4.3-absolute-heresy",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-21T19:14:12Z | ## 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": 636,
"end": 678,
"text": "Magidonia-24B-v4.3-absolute-heresy-i1-GGUF",
"label": "benchmark name",
"score": 0.7127508521080017
},
{
"start": 752,
"end": 791,
"text": "Magidonia-24B-v4.3-absolute-heresy-GGUF",
"label": "benchmark name",
"score": 0.617535173892974... |
magiccodingman/Qwen3-30B-A3B-Instruct-2507-unsloth-MagicQuant-Hybrid-GGUF | magiccodingman | 2025-12-06T04:40:00Z | 221 | 4 | null | [
"safetensors",
"gguf",
"qwen3_moe",
"mxfp4_hybrid",
"text-generation",
"quantized",
"cpu",
"gpu",
"mxfp4",
"mxfp4_moe",
"magicquant",
"magic_quant",
"IQ4_NL",
"conversational",
"base_model:unsloth/Qwen3-30B-A3B-Instruct-2507",
"base_model:quantized:unsloth/Qwen3-30B-A3B-Instruct-2507",... | text-generation | 2025-12-06T02:36:36Z | # MagicQuant GGUF Hybrids - Qwen3 30B A3B Instruct 2507
> **MagicQuant is an automated quantization, benchmarking, and evolutionary hybrid-GGUF search system for LLMs.**
Each release includes models optimized to outperform standard baseline quants (Q8, Q6, Q5, Q4).
If a baseline GGUF exists in this repo, the evolutio... | [
{
"start": 2,
"end": 12,
"text": "MagicQuant",
"label": "benchmark name",
"score": 0.94512540102005
},
{
"start": 61,
"end": 71,
"text": "MagicQuant",
"label": "benchmark name",
"score": 0.9514369964599609
},
{
"start": 633,
"end": 643,
"text": "MagicQuant... |
mradermacher/X-Coder-SFT-Qwen2.5-7B-i1-GGUF | mradermacher | 2026-01-11T06:23:43Z | 181 | 1 | transformers | [
"transformers",
"gguf",
"code",
"sft",
"competitive-programming",
"en",
"dataset:IIGroup/X-Coder-SFT-376k",
"base_model:IIGroup/X-Coder-SFT-Qwen2.5-7B",
"base_model:quantized:IIGroup/X-Coder-SFT-Qwen2.5-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversatio... | null | 2026-01-06T03:42:00Z | ## 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/gpt-oss-4B-i1-GGUF | mradermacher | 2025-12-06T19:07:35Z | 165 | 2 | transformers | [
"transformers",
"gguf",
"en",
"base_model:TroyDoesAI/gpt-oss-4B",
"base_model:quantized:TroyDoesAI/gpt-oss-4B",
"license:artistic-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-11-21T16:10:12Z | ## 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_... | [] |
HamzaSidhu786/wav2vec2-base-word-by-word-quran-asr | HamzaSidhu786 | 2024-07-23T04:23:58Z | 244 | 5 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/wav2vec2-base",
"base_model:finetune:facebook/wav2vec2-base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-21T10:04:45Z | <!-- 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. -->
# wav2vec2-base-word-by-word-quran-asr
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/f... | [
{
"start": 425,
"end": 429,
"text": "Loss",
"label": "evaluation metric",
"score": 0.6808133721351624
},
{
"start": 441,
"end": 444,
"text": "Wer",
"label": "evaluation metric",
"score": 0.9562827348709106
},
{
"start": 747,
"end": 760,
"text": "learning_r... |
bartowski/google_gemma-4-E2B-it-GGUF | bartowski | 2026-05-03T18:10:08Z | 147,471 | 29 | null | [
"gguf",
"image-text-to-text",
"base_model:google/gemma-4-E2B-it",
"base_model:quantized:google/gemma-4-E2B-it",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2026-04-02T16:00:20Z | ## Llamacpp imatrix Quantizations of gemma-4-E2B-it by google
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/b8746">b8746</a> for quantization.
Original model: https://huggingface.co/google/gemma-4-E2B-it
All quants made using ... | [] |
HuggingFaceTB/SmolLM3-3B-Base | HuggingFaceTB | 2025-08-14T16:41:36Z | 96,379 | 151 | transformers | [
"transformers",
"onnx",
"safetensors",
"smollm3",
"text-generation",
"transformers.js",
"en",
"fr",
"es",
"it",
"pt",
"zh",
"ar",
"ru",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-19T11:33:11Z | # SmolLM3
## Table of Contents
1. [Model Summary](#model-summary)
2. [How to use](#how-to-use)
3. [Evaluation](#evaluation)
4. [Training](#training)
5. [Limitations](#limitations)
6. [License](#l... | [] |
mradermacher/Gemini-Nano-Gemmafied-GGUF | mradermacher | 2024-08-25T23:09:22Z | 1,013 | 8 | transformers | [
"transformers",
"gguf",
"en",
"base_model:QuietImpostor/Gemini-Nano-Gemmafied",
"base_model:quantized:QuietImpostor/Gemini-Nano-Gemmafied",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2024-08-25T22:58:48Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/QuietImpostor/Gemini-Nano-Gemmafied
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at ... | [] |
mradermacher/aiqarus-agent-4b-i1-GGUF | mradermacher | 2026-03-09T11:45:37Z | 3,731 | 1 | transformers | [
"transformers",
"gguf",
"tool-calling",
"agent",
"enterprise",
"qwen3",
"qlora",
"fine-tuned",
"en",
"dataset:vericava/sft-tool-calling-structured-output-v1",
"dataset:interstellarninja/hermes_reasoning_tool_use",
"base_model:zeon01/aiqarus-agent-4b",
"base_model:quantized:zeon01/aiqarus-age... | null | 2026-02-28T08:07:59Z | ## 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": 615,
"end": 639,
"text": "aiqarus-agent-4b-i1-GGUF",
"label": "benchmark name",
"score": 0.6603098511695862
}
] |
TorpedoSoftware/Luau-Qwen3-4B-FIM-v0.1 | TorpedoSoftware | 2025-12-06T20:43:18Z | 574 | 4 | null | [
"safetensors",
"gguf",
"qwen3",
"roblox",
"luau",
"code",
"autocomplete",
"sft",
"en",
"dataset:TorpedoSoftware/the-luau-stack",
"arxiv:2207.14255",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"endpoints_compatible",
... | null | 2025-10-19T21:31:47Z | # Luau Qwen3 4B FIM v0.1
A specialized fine tune of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) trained specifically for FIM Luau code based on "Efficient Training of Language Models to Fill in the Middle" by [Mohammad Bavarian et al., 2022](https://arxiv.org/abs/2207.14255). Inst... | [] |
imvladikon/wav2vec2-xls-r-300m-hebrew | imvladikon | 2023-09-13T15:54:14Z | 247,358 | 5 | transformers | [
"transformers",
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"he",
"hf-asr-leaderboard",
"robust-speech-event",
"base_model:facebook/wav2vec2-xls-r-300m",
"base_model:finetune:facebook/wav2vec2-xls-r-300m",
"model-index",
"endpoints_compatib... | automatic-speech-recognition | 2022-03-02T23:29:05Z | <!-- 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. -->
# wav2vec2-xls-r-300m-hebrew
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/w... | [
{
"start": 1091,
"end": 1094,
"text": "WER",
"label": "evaluation metric",
"score": 0.6893898248672485
},
{
"start": 1123,
"end": 1126,
"text": "WER",
"label": "evaluation metric",
"score": 0.6505240797996521
},
{
"start": 1178,
"end": 1181,
"text": "WER",... |
AaryanK/GLM-4.7-GGUF | AaryanK | 2025-12-23T05:33:53Z | 224 | 14 | gguf | [
"gguf",
"text-generation-inference",
"glm",
"chat",
"agents",
"code",
"thinking",
"text-generation",
"en",
"zh",
"base_model:zai-org/GLM-4.7",
"base_model:quantized:zai-org/GLM-4.7",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-12-22T17:49:12Z | # GLM-4.7-GGUF
<div align="center">
<img src="https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg" width="15%"/>
</div>
> [!IMPORTANT]
> **I am currently looking for open positions!** 🤗
> If you find this model useful or are looking for a talented AI/LLM Engineer, please reach out to... | [
{
"start": 89,
"end": 96,
"text": "GLM-4.5",
"label": "benchmark name",
"score": 0.718136191368103
},
{
"start": 490,
"end": 497,
"text": "GLM-4.7",
"label": "benchmark name",
"score": 0.8385557532310486
},
{
"start": 530,
"end": 537,
"text": "GLM-4.7",
... |
BAAI/bge-base-zh-v1.5 | BAAI | 2023-10-12T03:35:51Z | 426,268 | 103 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"zh",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2023-09-12T05:21:53Z | <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... | [] |
mradermacher/Magidonia-24B-v4.3-heretic-v1.2-i1-GGUF | mradermacher | 2026-03-04T18:17:08Z | 4,876 | 2 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"mpoa",
"en",
"base_model:grayarea/Magidonia-24B-v4.3-heretic-v1.2",
"base_model:quantized:grayarea/Magidonia-24B-v4.3-heretic-v1.2",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-04T12:51:18Z | ## 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/ALIA-legal-administrative-7B-Instruct-i1-GGUF | mradermacher | 2026-02-19T08:31:37Z | 179 | 1 | transformers | [
"transformers",
"gguf",
"legal",
"administrative",
"spanish",
"es",
"dataset:SINAI/ALIA-legal-administrative-synthetic-instructions",
"base_model:SINAI/ALIA-legal-administrative-7B-Instruct",
"base_model:quantized:SINAI/ALIA-legal-administrative-7B-Instruct",
"license:apache-2.0",
"endpoints_com... | null | 2026-02-19T07:22:37Z | ## 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_... | [] |
LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct-AWQ | LGAI-EXAONE | 2026-02-06T06:14:59Z | 247 | 21 | transformers | [
"transformers",
"safetensors",
"exaone",
"text-generation",
"lg-ai",
"exaone-3.5",
"conversational",
"custom_code",
"en",
"ko",
"arxiv:2412.04862",
"license:other",
"4-bit",
"awq",
"region:us"
] | text-generation | 2024-12-01T11:17:55Z | <p align="center">
<img src="assets/EXAONE_Symbol+BI_3d.png", width="300", style="margin: 40 auto;">
<br>
# EXAONE-3.5-2.4B-Instruct-AWQ
## Introduction
We introduce EXAONE 3.5, a collection of instruction-tuned bilingual (English and Korean) generative models ranging from 2.4B to 32B parameters, developed and relea... | [] |
labhamlet/gramt-ambisonics | labhamlet | 2026-01-27T13:47:49Z | 143 | 1 | transformers | [
"transformers",
"safetensors",
"gramt-ambisonics",
"feature-extraction",
"audio",
"spatial",
"speech",
"custom_code",
"dataset:agkphysics/AudioSet",
"arxiv:2506.00934",
"license:mit",
"region:us"
] | feature-extraction | 2025-11-04T16:57:07Z | # Model Card for Model ID
GRAM (General Purpose Audio Representation Model) is trained on AudioSet with newly proposed naturalistic training methadology.
GRAMs utilize MWMAE (Multi-window multi-head attention), and RIR augmentations to achieve state-of-the-art results on downstream tasks such as FSD50K, ESC50, VL even... | [] |
mradermacher/Darkmere-8B-v0.1-GGUF | mradermacher | 2026-03-14T11:08:26Z | 553 | 1 | transformers | [
"transformers",
"gguf",
"mistral",
"heretic",
"uncensored",
"decensored",
"abliterated",
"roleplay",
"rp",
"creative-writing",
"en",
"base_model:0xA50C1A1/Darkmere-8B-v0.1",
"base_model:quantized:0xA50C1A1/Darkmere-8B-v0.1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
... | null | 2026-03-14T11:01:20Z | ## 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... | [] |
tensorblock/MiniMaxAI_SynLogic-7B-GGUF | tensorblock | 2026-01-27T21:13:50Z | 528 | 3 | transformers | [
"transformers",
"gguf",
"LLM",
"TensorBlock",
"GGUF",
"text-generation",
"en",
"dataset:MiniMaxAI/SynLogic",
"base_model:MiniMaxAI/SynLogic-7B",
"base_model:quantized:MiniMaxAI/SynLogic-7B",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-08-08T12:28:31Z | <div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
[](https://t... | [] |
uer/gpt2-chinese-cluecorpussmall | uer | 2023-10-17T15:21:48Z | 21,969 | 253 | transformers | [
"transformers",
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:2212.06385",
"text-generation-inference",
"endpoints_compatible",
"region:us",
"deploy:azure"
] | text-generation | 2022-03-02T23:29:05Z | # Chinese GPT2 Models
## Model description
The set of GPT2 models, except for GPT2-xlarge model, are pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658). The GPT2-xlarge model is pre-trained by [TencentPretrain](https://github.com/Tencent/Te... | [] |
mradermacher/MiniMax-M2.1-i1-GGUF | mradermacher | 2026-01-02T11:00:13Z | 2,342 | 4 | transformers | [
"transformers",
"gguf",
"en",
"base_model:MiniMaxAI/MiniMax-M2.1",
"base_model:quantized:MiniMaxAI/MiniMax-M2.1",
"license:other",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-29T02:31:32Z | ## 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_... | [] |
shunyalabs/zero-stt-hinglish | shunyalabs | 2025-12-12T13:53:42Z | 377 | 2 | null | [
"safetensors",
"whisper",
"Hinglish",
"Codeswitching",
"Speech-to-text",
"Indic",
"STT",
"automatic-speech-recognition",
"hi",
"en",
"dataset:ARTPARK-IISc/Vaani",
"dataset:ai4bharat/Kathbath",
"dataset:ai4bharat/Shrutilipi",
"base_model:openai/whisper-medium",
"base_model:finetune:openai... | automatic-speech-recognition | 2025-11-27T06:35:31Z | # Shunya Labs Hinglish ASR Model
We wanted to make ASR that could intuitively capture how conversational Hindi is actually spoken. On average, every 2 words out of 10 spoken in conversational Hindi are in English. Traditional ARS models are trained to handle one language at a time, which makes them too slow and inaccu... | [] |
MerlinSafety/Pluto | MerlinSafety | 2026-03-22T01:41:34Z | 229 | 4 | null | [
"safetensors",
"gguf",
"qwen3_5",
"code",
"reasoning",
"distillation",
"reinforcement-learning",
"long-context",
"claude-code",
"openai-codex",
"quantum-entropy",
"merlin-research",
"image-text-to-text",
"conversational",
"en",
"base_model:Qwen/Qwen3.5-9B-Base",
"base_model:quantized... | image-text-to-text | 2026-03-22T00:19:58Z | # Pluto
[](https://www.apache.org/licenses/LICENSE-2.0)
[![IBM Quantum](https://img.shields.io/b... | [
{
"start": 2,
"end": 7,
"text": "Pluto",
"label": "benchmark name",
"score": 0.6817876100540161
},
{
"start": 552,
"end": 557,
"text": "Pluto",
"label": "benchmark name",
"score": 0.7054900527000427
}
] |
bartowski/google_gemma-4-31B-it-GGUF | bartowski | 2026-05-03T20:15:16Z | 293,967 | 58 | null | [
"gguf",
"image-text-to-text",
"base_model:google/gemma-4-31B-it",
"base_model:quantized:google/gemma-4-31B-it",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | image-text-to-text | 2026-04-02T16:01:24Z | ## Llamacpp imatrix Quantizations of gemma-4-31B-it by google
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/b8746">b8746</a> for quantization.
Original model: https://huggingface.co/google/gemma-4-31B-it
All quants made using ... | [] |
mradermacher/A0l-12B-heretic-GGUF | mradermacher | 2026-03-04T08:24:53Z | 915 | 1 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"dataset:schneewolflabs/Athanorlite-DPO",
"base_model:nbeerbower/A0l-12B-heretic",
"base_model:quantized:nbeerbower/A0l-12B-heretic",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversation... | null | 2026-03-04T03:48:45Z | ## 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": 515,
"end": 535,
"text": "A0l-12B-heretic-GGUF",
"label": "benchmark name",
"score": 0.6015000343322754
}
] |
facebook/metaclip-2-worldwide-giant-378 | facebook | 2025-08-18T07:31:16Z | 9,662 | 11 | transformers | [
"transformers",
"safetensors",
"metaclip_2",
"zero-shot-image-classification",
"clip",
"multilingual",
"arxiv:2507.22062",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | zero-shot-image-classification | 2025-08-16T11:26:00Z | # Model Card for MetaCLIP 2 (worldwide)
MetaCLIP 2 (worldwide) was presented in [MetaCLIP 2: A Worldwide Scaling Recipe](https://huggingface.co/papers/2507.22062).
This checkpoint corresponds to "ViT-bigG-14-378-worldwide" of the [original implementation](https://github.com/facebookresearch/MetaCLIP).
## Install
Fi... | [] |
mradermacher/Kimi-VL-A3B-Instruct-GGUF | mradermacher | 2025-08-31T19:34:44Z | 567 | 2 | transformers | [
"transformers",
"gguf",
"agent",
"video",
"screenspot",
"long-context",
"en",
"base_model:moonshotai/Kimi-VL-A3B-Instruct",
"base_model:quantized:moonshotai/Kimi-VL-A3B-Instruct",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-31T17:41:39Z | ## 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... | [] |
numind/NuExtract-2.0-8B-GGUF | numind | 2025-09-26T14:28:49Z | 472 | 3 | transformers | [
"transformers",
"gguf",
"image-text-to-text",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2025-09-26T13:46:38Z | <p align="center">
<a href="https://nuextract.ai/">
<img src="logo_nuextract.svg" width="200"/>
</a>
</p>
<p align="center">
🖥️ <a href="https://nuextract.ai/">API / Platform</a>   |   📑 <a href="https://numind.ai/blog">Blog</a>   |   🗣️ <a href="https://discor... | [] |
Stephen-SMJ/DARE-R-Retriever | Stephen-SMJ | 2026-03-07T03:37:22Z | 117 | 2 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"retrieval",
"tool-use",
"llm-agent",
"r-language",
"en",
"arxiv:2603.04743",
"base_model:sentence-transformers/all-MiniLM-L6-v2",
"base_model:finetune:sentence-transformers/all-MiniLM-L6-v2",
"lic... | feature-extraction | 2026-02-26T13:48:02Z | 
DARE (Distribution-Aware Retrieval Embedding) is a specialized bi-encoder model designed to retrieve statistical and data analysis tools (R functions) based on **both user queries and conditional on... | [] |
onnx-community/Falcon-H1-Tiny-90M-Instruct-ONNX | onnx-community | 2026-03-30T17:14:32Z | 505 | 2 | transformers.js | [
"transformers.js",
"onnx",
"falcon_h1",
"text-generation",
"falcon-h1",
"edge",
"conversational",
"base_model:tiiuae/Falcon-H1-Tiny-90M-Instruct",
"base_model:quantized:tiiuae/Falcon-H1-Tiny-90M-Instruct",
"license:other",
"region:us"
] | text-generation | 2026-01-17T04:13:39Z | <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... | [] |
Writer/palmyra-mini-thinking-a-MLX-BF16 | Writer | 2025-09-11T19:14:41Z | 568 | 1 | mlx | [
"mlx",
"safetensors",
"qwen2",
"palmyra",
"thinking",
"reasoning",
"base_model:Writer/palmyra-mini-thinking-a",
"base_model:finetune:Writer/palmyra-mini-thinking-a",
"license:apache-2.0",
"region:us"
] | null | 2025-09-06T01:44:01Z | # Palmyra Mini Thinking A - MLX BF16
## Model Description
This is a bfloat16 precision version of the [palmyra-mini-thinking-a model](https://huggingface.co/Writer/palmyra-mini-thinking-a), optimized for Apple Silicon using the MLX framework. This model is based on the Qwen2 architecture and is specifically designed ... | [] |
prithivMLmods/Qwen-Image-Edit-2511-Midnight-Noir-Eyes-Spotlight | prithivMLmods | 2026-01-14T10:28:33Z | 3,158 | 4 | diffusers | [
"diffusers",
"lora",
"art",
"image-to-image",
"en",
"base_model:Qwen/Qwen-Image-Edit-2511",
"base_model:adapter:Qwen/Qwen-Image-Edit-2511",
"doi:10.57967/hf/7529",
"license:apache-2.0",
"region:us"
] | image-to-image | 2026-01-13T16:18:23Z | 
# **Qwen-Image-Edit-2511-Midnight-Noir-Eyes-Spotlight**
> Qwen-Image-Edit-2511-Midnight-Noir-Ey... | [] |
mradermacher/Firefly-V2Q-NonThinking-RP-i1-GGUF | mradermacher | 2026-03-10T09:00:09Z | 5,624 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"en",
"base_model:Guilherme34/Firefly-V2Q-NonThinking-RP",
"base_model:quantized:Guilherme34/Firefly-V2Q-NonThinking-RP",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-10T08:37:36Z | ## 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": 630,
"end": 664,
"text": "Firefly-V2Q-NonThinking-RP-i1-GGUF",
"label": "benchmark name",
"score": 0.725151538848877
},
{
"start": 738,
"end": 769,
"text": "Firefly-V2Q-NonThinking-RP-GGUF",
"label": "benchmark name",
"score": 0.6486042737960815
},
{
"s... |
llm-jp/llm-jp-3-150m | llm-jp | 2025-02-04T04:53:27Z | 1,846 | 4 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"en",
"ja",
"license:apache-2.0",
"text-generation-inference",
"region:us"
] | text-generation | 2025-01-27T04:26:44Z | # llm-jp-3-150m
LLM-jp-3 is the series of large language models developed by the [Research and Development Center for Large Language Models](https://llmc.nii.ac.jp/) at the [National Institute of Informatics](https://www.nii.ac.jp/en/).
This repository provides **llm-jp-3-150m** model.
For an overview of the LLM-jp-3... | [] |
Qodo/Qodo-Embed-1-1.5B | Qodo | 2025-02-24T15:09:11Z | 55,384 | 64 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"qwen2",
"feature-extraction",
"sentence-similarity",
"transformers",
"Qwen2",
"custom_code",
"base_model:Alibaba-NLP/gte-Qwen2-1.5B-instruct",
"base_model:finetune:Alibaba-NLP/gte-Qwen2-1.5B-instruct",
"license:other",
"text-embeddings-inference",
"en... | sentence-similarity | 2025-02-19T12:55:19Z | ## Qodo-Embed-1
**Qodo-Embed-1 is a state-of-the-art** code embedding model designed for retrieval tasks in the software development domain.
It is offered in two sizes: lite (1.5B) and medium (7B). The model is optimized for natural language-to-code and code-to-code retrieval, making it highly effective for applicatio... | [
{
"start": 499,
"end": 503,
"text": "COIR",
"label": "benchmark name",
"score": 0.7116899490356445
},
{
"start": 508,
"end": 512,
"text": "MTEB",
"label": "benchmark name",
"score": 0.622986376285553
},
{
"start": 1377,
"end": 1394,
"text": "similarity sco... |
capcheck/ai-image-detection | capcheck | 2025-12-06T03:52:02Z | 911 | 3 | null | [
"safetensors",
"vit",
"image-classification",
"vision",
"ai-detection",
"deepfake-detection",
"dataset:CIFAKE",
"base_model:dima806/ai_vs_real_image_detection",
"base_model:finetune:dima806/ai_vs_real_image_detection",
"license:apache-2.0",
"region:us"
] | image-classification | 2025-12-06T03:51:57Z | # CapCheck AI Image Detection
Vision Transformer (ViT) fine-tuned for detecting AI-generated images.
## Model Lineage & Attribution
This model builds on the work of others:
| Layer | Model | Author | License |
|-------|-------|--------|---------|
| Base Architecture | [google/vit-base-patch16-224-in21k](https://hug... | [] |
mradermacher/Darkidol-Gemma-4-E2B-it-i1-GGUF | mradermacher | 2026-04-18T09:45:59Z | 3,069 | 1 | transformers | [
"transformers",
"gguf",
"roleplay",
"gemma",
"gemma4",
"sillytavern",
"idol",
"pytorch",
"DarkIdol",
"Queen",
"any-to-any",
"OpenClaw",
"en",
"base_model:aifeifei798/Darkidol-Gemma-4-E2B-it",
"base_model:quantized:aifeifei798/Darkidol-Gemma-4-E2B-it",
"license:apache-2.0",
"endpoints... | any-to-any | 2026-04-09T05:59:22Z | ## 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": 467,
"end": 490,
"text": "Darkidol-Gemma-4-E2B-it",
"label": "benchmark name",
"score": 0.6975402235984802
},
{
"start": 627,
"end": 658,
"text": "Darkidol-Gemma-4-E2B-it-i1-GGUF",
"label": "benchmark name",
"score": 0.7705602645874023
},
{
"start": 732... |
nvidia/NV-Generate-MR-Brain | nvidia | 2026-04-08T16:45:19Z | 325 | 16 | null | [
"latent_diffusion",
"medical-imaging",
"diffusion",
"unconditional-image-generation",
"dataset:Forithmus/MR-RATE",
"arxiv:2508.05772",
"arxiv:2409.11169",
"license:other",
"region:us"
] | unconditional-image-generation | 2026-03-12T04:56:25Z | # NV-Generate-MR-Brain Overview
## Description:
NV-Generate-MR-Brain is a three-dimensional (3D) latent diffusion model designed to generate high-quality synthetic brain magnetic resonance imaging (MRI) images, achieving the highest resolution and best FID scores among comparable models. This model is specialized for ... | [
{
"start": 254,
"end": 264,
"text": "FID scores",
"label": "evaluation metric",
"score": 0.701934814453125
}
] |
HauhauCS/Qwen3.5-27B-Uncensored-HauhauCS-Aggressive | HauhauCS | 2026-04-05T19:00:48Z | 253,512 | 274 | null | [
"gguf",
"uncensored",
"qwen3.5",
"qwen",
"en",
"zh",
"multilingual",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-05T22:13:03Z | # Qwen3.5-27B-Uncensored-HauhauCS-Aggressive
> **[Join the Discord](https://discord.gg/SZ5vacTXYf)** for updates, roadmaps, projects, or just to chat.
Qwen3.5-27B uncensored by HauhauCS.
## About
**0/465 refusals.** Fully uncensored with zero capability loss.
No changes to datasets or capabilities. Fully functiona... | [] |
mradermacher/gpt-oss-120b-Distill-Qwen3-4B-Thinking-i1-GGUF | mradermacher | 2025-12-05T12:04:58Z | 269 | 1 | transformers | [
"transformers",
"gguf",
"en",
"zh",
"dataset:Jackrong/Natural-Reasoning-gpt-oss-120B-S1",
"dataset:Jackrong/ShareGPT-gpt-oss-120B-reasoning",
"base_model:Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking",
"base_model:quantized:Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking",
"license:apache-2.0",
... | null | 2025-11-23T09:53:36Z | ## 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_... | [] |
unsloth/Z-Image-GGUF | unsloth | 2026-01-28T06:04:22Z | 14,798 | 135 | ggml | [
"ggml",
"gguf",
"unsloth",
"quantized",
"text-to-image",
"en",
"arxiv:2511.22699",
"base_model:Tongyi-MAI/Z-Image",
"base_model:quantized:Tongyi-MAI/Z-Image",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-01-27T23:10:23Z | This is a GGUF quantized version of [Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image). <br>
unsloth/Z-Image-GGUF uses [Unsloth Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) methodology for SOTA performance.
- Important layers are upcasted to higher precision.
- Uses tooling from [ComfyUI-GGU... | [] |
unsloth/GLM-4.5-GGUF | unsloth | 2025-12-26T05:09:51Z | 1,065 | 49 | transformers | [
"transformers",
"gguf",
"text-generation",
"en",
"zh",
"base_model:zai-org/GLM-4.5",
"base_model:quantized:zai-org/GLM-4.5",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | text-generation | 2025-08-05T09:21:46Z | # GLM-4.5
<div align="center">
<img src=https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg width="15%"/>
</div>
<p align="center">
👋 Join our <a href="https://discord.gg/QR7SARHRxK" target="_blank">Discord</a> community.
<br>
📖 Check out the GLM-4.5 <a href="https://z.ai... | [] |
BAAI/AltCLIP | BAAI | 2025-04-16T07:02:37Z | 90,055 | 32 | transformers | [
"transformers",
"pytorch",
"altclip",
"zero-shot-image-classification",
"Zero-Shot Image Classification",
"bilingual",
"en",
"English",
"zh",
"Chinese",
"arxiv:2211.06679",
"license:creativeml-openrail-m",
"region:us"
] | zero-shot-image-classification | 2022-11-15T03:22:10Z | # AltCLIP
| 名称 Name | 任务 Task | 语言 Language(s) | 模型 Model | Github |
|:------------------:|:----------:|:-------------------:|:--------:|:------:|
| AltCLIP | text-image representation| 中英文 Chinese&English | CLIP | [FlagAI](https://github.com/FlagAI-Open/FlagAI) |
## 简介 Brief Introduction
... | [] |
janhq/Jan-v3-4B-base-instruct-gguf | janhq | 2026-01-28T15:57:00Z | 328,030 | 51 | transformers | [
"transformers",
"gguf",
"code",
"text-generation",
"en",
"base_model:janhq/Jan-v3-4B-base-instruct",
"base_model:quantized:janhq/Jan-v3-4B-base-instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-01-20T06:49:01Z | # Jan-v3-4B-base-instruct: a 4B baseline model for fine-tuning
[](https://github.com/janhq/jan)
[](https://opensource.org/licenses/Apache-2.0)
[![Jan App](https://img.shields.i... | [
{
"start": 921,
"end": 929,
"text": "Jan-Code",
"label": "benchmark name",
"score": 0.6577142477035522
}
] |
mradermacher/gemma-3-12b-it-heretic-GGUF | mradermacher | 2025-11-23T15:26:51Z | 3,426 | 13 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:p-e-w/gemma-3-12b-it-heretic",
"base_model:quantized:p-e-w/gemma-3-12b-it-heretic",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-23T14:42:59Z | ## 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... | [] |
Qwen/Qwen3-32B-GGUF | Qwen | 2025-05-09T07:16:46Z | 26,296 | 66 | null | [
"gguf",
"text-generation",
"arxiv:2309.00071",
"base_model:Qwen/Qwen3-32B",
"base_model:quantized:Qwen/Qwen3-32B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-05-01T10:23:45Z | # Qwen3-32B-GGUF
<a href="https://chat.qwen.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Qwen3 Highlights
Qwen3 is the latest generation of large language... | [] |
EntermindAI/Rukun-32B-V | EntermindAI | 2026-03-19T07:16:30Z | 811 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"qwen2.5",
"lora",
"malaysia",
"safety",
"moderation",
"rukun-negara",
"multilingual",
"conversational",
"en",
"ms",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-32B-Instruct",
"license:other",
"... | text-generation | 2026-02-02T01:56:34Z | # Rukun Ready AI (Rukun-32B-v1.5)
Rukun Ready AI is a Malaysia-aligned structured validation model built on `Qwen/Qwen2.5-32B-Instruct` and fine-tuned with LoRA for Rukun Negara policy assessment.
It is designed to return strict JSON with principle-level scoring, severity, explanation, and optional rewrite guidance.
... | [] |
smcleish/Recurrent-OLMo-2-0425-train-recurrence-32 | smcleish | 2025-11-11T13:15:25Z | 388 | 2 | transformers | [
"transformers",
"safetensors",
"huginn_raven",
"text-generation",
"causal-lm",
"custom_code",
"en",
"dataset:nvidia/Nemotron-CC-Math-v1",
"arxiv:2511.07384",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-11-08T19:08:32Z | # Recurrent-OLMo-2-0425-train-recurrence-32
Recurrent-OLMo-2-0425-train-recurrence-32 is part of the [Retrofitting Recurrence](https://hf.co/collections/tomg-group-umd/retrofitting-recurrence) set of models. A set of depth recurrent models trained by taking layers from pretrained feedforward language models ([link to p... | [] |
tiiuae/Falcon-H1-34B-Instruct | tiiuae | 2025-07-31T04:04:08Z | 1,270 | 52 | transformers | [
"transformers",
"safetensors",
"falcon_h1",
"text-generation",
"falcon-h1",
"conversational",
"ar",
"cs",
"de",
"en",
"es",
"fr",
"hi",
"it",
"ja",
"ko",
"nl",
"pl",
"pt",
"ro",
"ru",
"sv",
"ur",
"zh",
"arxiv:2507.22448",
"base_model:tiiuae/Falcon-H1-34B-Base",
"b... | text-generation | 2025-05-01T15:44:45Z | <img src="https://huggingface.co/datasets/tiiuae/documentation-images/resolve/main/falcon_mamba/falcon-h1-logo.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... | [] |
mradermacher/LFM2-8B-A1B-absolute-heresy-MPOA-i1-GGUF | mradermacher | 2026-02-16T09:43:29Z | 750 | 2 | transformers | [
"transformers",
"gguf",
"liquid",
"lfm2",
"edge",
"moe",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"base_model:MuXodious/LFM2-8B-A1B-absolute-heresy-MPOA",
"base_model:quantized:MuXodious/LFM2-8B-A1B-absolute-heresy-MP... | null | 2026-02-15T18:57:41Z | ## 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": 634,
"end": 674,
"text": "LFM2-8B-A1B-absolute-heresy-MPOA-i1-GGUF",
"label": "benchmark name",
"score": 0.64455646276474
}
] |
nvidia/parakeet-tdt-1.1b | nvidia | 2025-12-03T22:27:57Z | 18,918 | 114 | nemo | [
"nemo",
"automatic-speech-recognition",
"speech",
"audio",
"Transducer",
"TDT",
"FastConformer",
"Conformer",
"pytorch",
"NeMo",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"dataset:fisher_corpus",
"dataset:Switchboard-1",
"dataset:WSJ-0",
"dataset:WSJ-1",
"dataset:Natio... | automatic-speech-recognition | 2024-01-25T02:05:06Z | # Parakeet TDT 1.1B (en)
<style>
img {
display: inline;
}
</style>
[](#model-architecture)
| [](#model-architecture)
| [![Language](https... | [] |
NikolayKozloff/translategemma-12b-it-Q8_0-GGUF | NikolayKozloff | 2026-01-15T18:39:09Z | 238 | 3 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"base_model:google/translategemma-12b-it",
"base_model:quantized:google/translategemma-12b-it",
"license:gemma",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-01-15T18:38:19Z | # NikolayKozloff/translategemma-12b-it-Q8_0-GGUF
This model was converted to GGUF format from [`google/translategemma-12b-it`](https://huggingface.co/google/translategemma-12b-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 ca... | [] |
mradermacher/tvall43-Qwen3.5-4B-heretic-v2-GGUF | mradermacher | 2026-04-05T19:09:40Z | 647 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:CCSSNE/tvall43-Qwen3.5-4B-heretic-v2",
"base_model:quantized:CCSSNE/tvall43-Qwen3.5-4B-heretic-v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-24T16:32:57Z | ## 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: 1 -->
static ... | [] |
OpenMed/OpenMed-NER-DNADetect-SuperClinical-434M | OpenMed | 2025-08-05T09:35:08Z | 77,427 | 1 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"token-classification",
"named-entity-recognition",
"biomedical-nlp",
"protein-recognition",
"gene-recognition",
"molecular-biology",
"genomics",
"dna",
"rna",
"cell_line",
"cell_type",
"protein",
"en",
"arxiv:2508.01630",
"license:apach... | token-classification | 2025-07-16T19:23:01Z | # 🧬 [OpenMed-NER-DNADetect-SuperClinical-434M](https://huggingface.co/OpenMed/OpenMed-NER-DNADetect-SuperClinical-434M)
**Specialized model for Biomedical Entity Recognition - Proteins, DNA, RNA, cell lines, and cell types**
[](https://opensource.... | [
{
"start": 1420,
"end": 1439,
"text": "clinical benchmarks",
"label": "benchmark name",
"score": 0.7347123026847839
}
] |
thelamapi/next-ocr | thelamapi | 2026-03-01T18:17:33Z | 6,062 | 19 | transformers | [
"transformers",
"safetensors",
"gguf",
"qwen3_vl",
"image-text-to-text",
"text-generation-inference",
"unsloth",
"trl",
"sft",
"chemistry",
"code",
"climate",
"art",
"biology",
"finance",
"legal",
"music",
"medical",
"agent",
"conversational",
"en",
"ab",
"aa",
"ae",
... | image-text-to-text | 2025-11-12T18:07:47Z | <img src='bannerocr.png'>
# 🖼️ Next OCR 8B
### *Compact OCR AI — Accurate, Fast, Multilingual, Math-Optimized*
[](https://opensource.org/licenses/MIT)
[]()
[![Huggin... | [] |
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