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 |
|---|---|---|---|---|---|---|---|---|---|---|
mssfj/Qwen3.5-9B-GPTQ-INT8 | mssfj | 2026-04-05T15:34:32Z | 2,288 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3_5_text",
"text-generation",
"qwen",
"gptq",
"quantized",
"math",
"causal-lm",
"conversational",
"en",
"base_model:Qwen/Qwen3.5-9B",
"base_model:quantized:Qwen/Qwen3.5-9B",
"license:apache-2.0",
"endpoints_compatible",
"8-bit",
"region:us"
] | text-generation | 2026-03-16T04:04:59Z | # Qwen3.5-9B-GPTQ-INT8
This model is a GPTQ-quantized version of `Qwen/Qwen3.5-9B` with a normalized text-only `config.json`.
## Quantization
- Method: GPTQ
- Bits: 8
- Group size: 128
- desc_act: False
- damp_percent: 0.1
- Calibration preset: math_qa_cot
- Calibration dataset: `zwhe99/DeepMath-103K` split `train`
... | [
{
"start": 208,
"end": 220,
"text": "damp_percent",
"label": "evaluation metric",
"score": 0.6057606935501099
},
{
"start": 222,
"end": 225,
"text": "0.1",
"label": "evaluation metric",
"score": 0.7141847014427185
},
{
"start": 291,
"end": 304,
"text": "De... |
RichardErkhov/Sao10K_-_L3-8B-Stheno-v3.2-gguf | RichardErkhov | 2024-06-25T08:22:02Z | 441 | 3 | null | [
"gguf",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2024-06-25T04:05:03Z | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
L3-8B-Stheno-v3.2 - GGUF
- Model creator: https://huggingface.co/Sao10K/
- Original model: https://huggingface.co/Sao10K/L3-... | [] |
mradermacher/Qwen3-VL-4B-Instruct-heretic-i1-GGUF | mradermacher | 2025-12-28T00:38:09Z | 166 | 1 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:SergiusFlavius/Qwen3-VL-4B-Instruct-heretic",
"base_model:quantized:SergiusFlavius/Qwen3-VL-4B-Instruct-heretic",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversat... | null | 2025-12-27T05:06:00Z | ## 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_... | [] |
1-800-BAD-CODE/punctuation_fullstop_truecase_english | 1-800-BAD-CODE | 2023-03-19T21:35:48Z | 38,649 | 15 | generic | [
"generic",
"onnx",
"text2text-generation",
"punctuation",
"true-casing",
"sentence-boundary-detection",
"nlp",
"en",
"license:apache-2.0",
"region:us"
] | null | 2023-03-11T22:21:22Z | # Model Overview
This model accepts as input lower-cased, unpunctuated English text and performs in one pass punctuation restoration, true-casing (capitalization), and sentence boundary detection (segmentation).
In contast to many similar models, this model can predict punctuated acronyms (e.g., "U.S.") via a special ... | [] |
Olafangensan/GLM-4.7-Flash-heretic-GGUF | Olafangensan | 2026-01-21T17:39:24Z | 198 | 5 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"autoquant",
"text-generation",
"en",
"zh",
"arxiv:2508.06471",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-01-21T15:01:32Z | # NOTE: These GGUF files were created after the "sigmoid fix" for this model was merged into the main llama.cpp branch.
Fix in question: [github](https://github.com/ggml-org/llama.cpp/pull/18980)
---
# This is a decensored version of [zai-org/GLM-4.7-Flash](https://huggingface.co/zai-org/GLM-4.7-Flash), made using [... | [
{
"start": 517,
"end": 548,
"text": "attn.o_proj.max_weight_position",
"label": "evaluation metric",
"score": 0.6537140011787415
},
{
"start": 651,
"end": 675,
"text": "mlp.down_proj.max_weight",
"label": "evaluation metric",
"score": 0.7195148468017578
},
{
"star... |
mradermacher/Qwen3.5-2B-Claude-4.6-Opus-Reasoning-Distilled-heretic-v1-i1-GGUF | mradermacher | 2026-04-18T13:03:36Z | 3,685 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"qwen",
"qwen3.5",
"qwen3.5-2B",
"reasoning",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:tvall43/Qwen3.5-2B-Claude-4.6-Opus-Reasoning-Distilled-heretic-v1",
"base_model:quantized:tvall43/Qwen3.5-2B-Claude-4.6-Opus-Reasoning-Di... | null | 2026-03-25T06:24:32Z | ## 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": 658,
"end": 723,
"text": "Qwen3.5-2B-Claude-4.6-Opus-Reasoning-Distilled-heretic-v1-i1-GGUF",
"label": "benchmark name",
"score": 0.6337454915046692
},
{
"start": 797,
"end": 859,
"text": "Qwen3.5-2B-Claude-4.6-Opus-Reasoning-Distilled-heretic-v1-GGUF",
"label": "b... |
nvidia/Qwen2.5-VL-7B-Instruct-FP8 | nvidia | 2025-12-12T03:46:17Z | 542 | 7 | Model Optimizer | [
"Model Optimizer",
"safetensors",
"qwen2_5_vl",
"nvidia",
"ModelOpt",
"quantized",
"FP8",
"fp8",
"text-generation",
"conversational",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-VL-7B-Instruct",
"license:other",
"modelopt",
"region:us"
] | text-generation | 2025-09-10T03:03:59Z | # Model Overview
## Description:
The NVIDIA Qwen2.5-VL-7B-Instruct-FP8 model is the quantized version of Alibaba's Qwen2.5-VL-7B-Instruct model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check [here](https://huggingface.co/Qwen/Qwen2.5-VL-7... | [] |
onnx-community/Supertonic-TTS-2-ONNX | onnx-community | 2026-01-20T18:14:41Z | 1,251 | 6 | transformers.js | [
"transformers.js",
"onnx",
"supertonic",
"text-to-speech",
"en",
"ko",
"es",
"pt",
"fr",
"base_model:Supertone/supertonic-2",
"base_model:quantized:Supertone/supertonic-2",
"license:openrail",
"region:us"
] | text-to-speech | 2026-01-06T17:32:08Z | ## Usage
### Transformers.js
If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
```bash
npm i @huggingface/transformers
```
You can then generate audio as follows:
```... | [] |
facebook/audiogen-medium | facebook | 2024-03-12T10:47:07Z | 24,660 | 142 | audiocraft | [
"audiocraft",
"audiogen",
"arxiv:2209.15352",
"arxiv:2306.05284",
"license:cc-by-nc-4.0",
"region:us"
] | null | 2023-07-26T19:28:41Z | # AudioGen - Medium - 1.5B
AudioGen is an autoregressive transformer LM that synthesizes general audio conditioned on text (Text-to-Audio).
Internally, AudioGen operates over discrete representations learnt from the raw waveform, using an EnCodec tokenizer.
AudioGen was presented at [AudioGen: Textually Guided Audio... | [] |
mradermacher/Qwen3.5-4B-Safety-Thinking-GGUF | mradermacher | 2026-03-11T11:01:00Z | 1,084 | 1 | transformers | [
"transformers",
"gguf",
"qwen3.5",
"ai-safety",
"reasoning",
"thinking",
"alignment",
"sft",
"en",
"base_model:MerlinSafety/Qwen3.5-4B-Safety-Thinking",
"base_model:quantized:MerlinSafety/Qwen3.5-4B-Safety-Thinking",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversatio... | null | 2026-03-11T10:40:56Z | ## 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 ... | [] |
apple/OpenELM-3B | apple | 2025-02-28T18:31:38Z | 283 | 130 | transformers | [
"transformers",
"safetensors",
"openelm",
"text-generation",
"custom_code",
"arxiv:2404.14619",
"license:apple-amlr",
"region:us"
] | text-generation | 2024-04-12T21:48:54Z | # OpenELM
*Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, Mohammad Rastegari*
We introduce **OpenELM**, a family of **Open** **E**fficient **L**anguage **M**odels. OpenELM uses a layer-wise scaling strategy ... | [] |
Alibaba-AAIG/YuFeng-XGuard-Reason-0.6B | Alibaba-AAIG | 2026-02-04T03:33:17Z | 161 | 3 | null | [
"safetensors",
"qwen3",
"arxiv:2601.15588",
"region:us"
] | null | 2025-12-29T02:34:14Z | <p align="center">
<img src="./xguard_banner.png" alt="Xguard Banner" width=100%/>
</p>
<div align="center">
<h1 style="margin: 0;">YuFeng-XGuard: A Reasoning-Centric, Interpretable, and Flexible Guardrail Model for Large Language Models</h1>
</div>
<p align="center">
  🤗 <a href="https://huggi... | [
{
"start": 1556,
"end": 1588,
"text": "multilingual risk identification",
"label": "benchmark name",
"score": 0.625262975692749
}
] |
unsloth/DeepSeek-R1-Distill-Llama-8B-GGUF | unsloth | 2025-05-10T13:04:41Z | 38,341 | 295 | transformers | [
"transformers",
"gguf",
"llama",
"text-generation",
"deepseek",
"unsloth",
"llama-3",
"meta",
"en",
"arxiv:2501.12948",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"license:llama3.1",
"endpoints_compatible",
"reg... | text-generation | 2025-01-20T13:04:25Z | <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/GUI-Libra-4B-GGUF | mradermacher | 2026-03-01T07:41:38Z | 903 | 1 | transformers | [
"transformers",
"gguf",
"VLM",
"GUI",
"agent",
"en",
"dataset:GUI-Libra/GUI-Libra-81K-RL",
"dataset:GUI-Libra/GUI-Libra-81K-SFT",
"base_model:GUI-Libra/GUI-Libra-4B",
"base_model:quantized:GUI-Libra/GUI-Libra-4B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
... | null | 2026-02-28T08:41:08Z | ## 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... | [] |
HuggingFaceTB/cosmo-1b | HuggingFaceTB | 2024-07-08T14:47:31Z | 240 | 134 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:HuggingFaceTB/cosmopedia",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-02-19T16:14:36Z | # Model Summary
This is a 1.8B model trained on [Cosmopedia](https://huggingface.co/datasets/HuggingFaceTB/cosmopedia) synthetic dataset.
# Training dataset
The training corpus consisted of 30B tokens, 25B of which are synthetic from Cosmopedia. Since we didn't explore the synthetic generation of code, we augmented th... | [] |
bartowski/moonshotai_Kimi-K2.5-GGUF | bartowski | 2026-02-17T17:00:24Z | 13,529 | 11 | null | [
"gguf",
"image-text-to-text",
"base_model:moonshotai/Kimi-K2.5",
"base_model:quantized:moonshotai/Kimi-K2.5",
"license:other",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | image-text-to-text | 2026-02-11T20:27:32Z | ## Llamacpp imatrix Quantizations of Kimi-K2.5 by moonshotai
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/b8003">b8003</a> for quantization.
Original model: https://huggingface.co/moonshotai/Kimi-K2.5
All quants made using im... | [] |
HuggingFaceH4/starchat-alpha | HuggingFaceH4 | 2023-06-08T21:15:30Z | 1,650 | 231 | transformers | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"gpt_bigcode",
"text-generation",
"code",
"en",
"dataset:OpenAssistant/oasst1",
"dataset:databricks/databricks-dolly-15k",
"license:bigcode-openrail-m",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2023-05-09T08:57:06Z | # Model Card for StarChat Alpha
<!-- Provide a quick summary of what the model is/does. -->
_Note, you may be interested in the Beta version of StarChat [here](https://huggingface.co/HuggingFaceH4/starchat-beta)._
StarChat is a series of language models that are fine-tuned from StarCoder to act as helpful coding assi... | [] |
facebook/mms-tts-orm | facebook | 2023-09-01T13:22:36Z | 5,494 | 7 | transformers | [
"transformers",
"pytorch",
"safetensors",
"vits",
"text-to-audio",
"mms",
"text-to-speech",
"arxiv:2305.13516",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | text-to-speech | 2023-09-01T13:22:08Z | ---
license: cc-by-nc-4.0
tags:
- mms
- vits
pipeline_tag: text-to-speech
---
# Massively Multilingual Speech (MMS): Oromo Text-to-Speech
This repository contains the **Oromo (orm)** language text-to-speech (TTS) model checkpoint.
This model is part of Facebook's [Massively Multilingual Speech](https://arxiv.org/abs... | [] |
ovedrive/Qwen-Image-Edit-2509-4bit | ovedrive | 2025-09-23T22:50:14Z | 16,265 | 17 | diffusers | [
"diffusers",
"safetensors",
"image-to-image",
"en",
"zh",
"arxiv:2508.02324",
"base_model:Qwen/Qwen-Image-Edit-2509",
"base_model:quantized:Qwen/Qwen-Image-Edit-2509",
"license:apache-2.0",
"diffusers:QwenImageEditPlusPipeline",
"region:us"
] | image-to-image | 2025-09-23T22:44:58Z | This is an NF4 quantized model of Qwen-image-edit-2509 so it can run on GPUs using 20GB VRAM. You can run it on lower VRAM like 16GB.
There were other NF4 models but they made the mistake of blindly quantizing all layers in the transformer.
This one does not. We retain some layers at full precision in order to ensure... | [] |
mradermacher/gpt-oss-20b-heretic-scanner-V1-2-i1-GGUF | mradermacher | 2025-12-11T19:13:57Z | 147 | 1 | transformers | [
"transformers",
"gguf",
"vllm",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:arnomatic/gpt-oss-20b-heretic-scanner-V1-2",
"base_model:quantized:arnomatic/gpt-oss-20b-heretic-scanner-V1-2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"c... | null | 2025-12-11T13:48:55Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: MXFP4_MOE 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 ... | [] |
caiovicentino1/Qwopus3.5-9B-v3-PolarQuant-Q5 | caiovicentino1 | 2026-04-08T18:56:38Z | 1,703 | 5 | null | [
"safetensors",
"qwen3_5",
"polarquant",
"gptq",
"int4",
"qwen3.5",
"vllm",
"marlin",
"text-generation",
"conversational",
"arxiv:2603.29078",
"base_model:Jackrong/Qwopus3.5-9B-v3",
"base_model:quantized:Jackrong/Qwopus3.5-9B-v3",
"license:apache-2.0",
"model-index",
"4-bit",
"region:... | text-generation | 2026-03-31T23:11:51Z | # 🧊 Qwopus3.5-9B-v3 — GPTQ Calibrated INT4
> **9B hybrid model (Qwen3.5 architecture) quantized to INT4** with GPTQ calibration. Loads natively in vLLM with Marlin kernel. 113 tok/s on RTX 3090.
## 🏆 NEW: PolarQuant v7 — INT4 that BEATS BF16
> **We found the optimal config: `group_size=64` + FOEM = 67.07% HumanEva... | [
{
"start": 100,
"end": 104,
"text": "INT4",
"label": "evaluation metric",
"score": 0.6240164637565613
},
{
"start": 158,
"end": 164,
"text": "Marlin",
"label": "benchmark name",
"score": 0.6105073690414429
},
{
"start": 624,
"end": 630,
"text": "Marlin",
... |
mradermacher/MS3.2-PaintedFantasy-v4-24B-absolute-heresy-i1-GGUF | mradermacher | 2026-02-16T23:36:39Z | 190 | 2 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"dataset:zerofata/Instruct-Anime",
"dataset:zerofata/Roleplay-Anime-Characters",
"dataset:zerofata/Instruct-Anime-CreativeWriting",
"dataset:zerofata/Summaries-Anime-FandomPages",
"dataset:CyberNative/Code_Vuln... | null | 2026-02-16T21:19:46Z | ## 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_... | [] |
manycore-research/SpatialLM1.1-Llama-1B | manycore-research | 2025-09-23T03:04:28Z | 400 | 16 | transformers | [
"transformers",
"safetensors",
"spatiallm_llama",
"text-generation",
"conversational",
"arxiv:2506.07491",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-1B-Instruct",
"license:llama3.2",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-06-08T14:31:19Z | # SpatialLM1.1-Llama-1B
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<picture>
<source srcset="https://cdn-uploads.huggingface.co/production/uploads/63efbb1efc92a63ac81126d0/_dK14CT3do8rBG3QrHUjN.png" media=... | [] |
qualcomm/Shufflenet-v2 | qualcomm | 2026-04-28T06:47:48Z | 136 | 1 | pytorch | [
"pytorch",
"android",
"image-classification",
"arxiv:1807.11164",
"license:other",
"region:us"
] | image-classification | 2024-02-25T23:05:43Z | 
# Shufflenet-v2: Optimized for Qualcomm Devices
ShufflenetV2 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more com... | [] |
Qwen/Qwen3-VL-4B-Thinking-FP8 | Qwen | 2025-11-26T13:18:21Z | 1,633 | 30 | transformers | [
"transformers",
"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-4B-Thinking",
"base_model:quantized:Qwen/Qwen3-VL-4B-Thinking",
"license:apache-2.0",
"endpoints_compat... | image-text-to-text | 2025-10-11T09:27:37Z | <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-4B-Thinking-FP8
> This repository contains an FP8 quantized version of t... | [
{
"start": 492,
"end": 511,
"text": "performance metrics",
"label": "evaluation metric",
"score": 0.6081159710884094
}
] |
Unbabel/TowerInstruct-13B-v0.1 | Unbabel | 2024-05-08T15:00:54Z | 1,303 | 35 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"translation",
"en",
"de",
"fr",
"zh",
"pt",
"nl",
"ru",
"ko",
"it",
"es",
"arxiv:2402.17733",
"license:cc-by-nc-4.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | translation | 2024-01-29T10:39:36Z | # Model Card for TowerInstruct-13B-v0.1
## Model Details
### Model Description
TowerInstruct-13B is a language model that results from fine-tuning TowerBase on the TowerBlocks supervised fine-tuning dataset. TowerInstruct-13B-v0.1 is the first model in the series.
The model is trained to handle several translation-... | [] |
unsloth/gte-modernbert-base | unsloth | 2026-01-22T14:29:17Z | 226 | 1 | transformers | [
"transformers",
"pytorch",
"onnx",
"safetensors",
"modernbert",
"feature-extraction",
"sentence-transformers",
"mteb",
"embedding",
"transformers.js",
"text-embeddings-inference",
"sentence-similarity",
"en",
"arxiv:2308.03281",
"base_model:answerdotai/ModernBERT-base",
"base_model:fin... | sentence-similarity | 2026-01-22T14:29:11Z | # gte-modernbert-base
We are excited to introduce the `gte-modernbert` series of models, which are built upon the latest modernBERT pre-trained encoder-only foundation models. The `gte-modernbert` series models include both text embedding models and rerank models.
The `gte-modernbert` models demonstrates competitive ... | [
{
"start": 506,
"end": 510,
"text": "MTEB",
"label": "benchmark name",
"score": 0.6609060168266296
},
{
"start": 512,
"end": 516,
"text": "LoCO",
"label": "benchmark name",
"score": 0.6963608860969543
},
{
"start": 522,
"end": 526,
"text": "COIR",
"lab... |
tokyotech-llm/Swallow-MS-7b-v0.1 | tokyotech-llm | 2024-08-17T09:14:54Z | 210 | 29 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"en",
"ja",
"arxiv:2404.17733",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-generation | 2024-02-01T01:12:16Z | # Swallow-MS-7b-v0.1
Our Swallow-MS-7b-v0.1 model has undergone continual pre-training from the Mistral-7B-v0.1, primarily with the addition of Japanese language data.
# Model Release Updates
We are excited to share the release schedule for our latest models:
- **April 26, 2024**: Released the [Swallow-MS-7b-instru... | [
{
"start": 1205,
"end": 1212,
"text": "Average",
"label": "evaluation metric",
"score": 0.8278328776359558
}
] |
mradermacher/GLM-4.6-REAP-218B-A32B-i1-GGUF | mradermacher | 2025-12-05T18:46:12Z | 497 | 6 | transformers | [
"transformers",
"gguf",
"glm",
"MOE",
"pruning",
"compression",
"en",
"base_model:cerebras/GLM-4.6-REAP-218B-A32B",
"base_model:quantized:cerebras/GLM-4.6-REAP-218B-A32B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-11-01T14:04:58Z | ## 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": 623,
"end": 653,
"text": "GLM-4.6-REAP-218B-A32B-i1-GGUF",
"label": "benchmark name",
"score": 0.6919608116149902
}
] |
mradermacher/Qwen3-30B-A3B-YOYO-Thinking-Chimera-i1-GGUF | mradermacher | 2026-01-07T02:19:26Z | 152 | 1 | transformers | [
"transformers",
"gguf",
"merge",
"en",
"zh",
"base_model:YOYO-AI/Qwen3-30B-A3B-YOYO-Thinking-Chimera",
"base_model:quantized:YOYO-AI/Qwen3-30B-A3B-YOYO-Thinking-Chimera",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-06T13:27:50Z | ## 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_... | [] |
ubergarm/GLM-5-GGUF | ubergarm | 2026-02-15T19:54:20Z | 549 | 16 | null | [
"gguf",
"imatrix",
"conversational",
"glm_moe_dsa",
"ik_llama.cpp",
"text-generation",
"en",
"zh",
"base_model:zai-org/GLM-5",
"base_model:quantized:zai-org/GLM-5",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-14T21:35:53Z | ## `ik_llama.cpp` imatrix Quantizations of zai-org/GLM-5
*NOTE* `ik_llama.cpp` can also run your existing GGUFs from bartowski, unsloth, mradermacher, etc if you want to try it out before downloading my quants.
Some of ik's new quants are supported with [Nexesenex/croco.cpp](https://github.com/Nexesenex/croco.cpp) for... | [] |
DavidAU/Qwen3.6-27B-NEO-CODE-Di-IMatrix-MAX-GGUF | DavidAU | 2026-04-30T07:47:43Z | 25,940 | 40 | null | [
"gguf",
"benchmarks",
"bfloat16",
"all use cases",
"imatrix",
"neo imatrix",
"duel imatrix",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"roman... | image-text-to-text | 2026-04-23T08:05:02Z | <small><font color="red">All Optimized Quants BENCHMARKED (5 metrics):</font> You know exactly how strong each NEO-CODE quant is relative to full precision model.
IQ4XS stands out at 94% of full precision at 1/4 the size of the full model. Then there are the Q6 and Q8, with the latter hitting 98.38% (of full precision... | [
{
"start": 191,
"end": 205,
"text": "full precision",
"label": "evaluation metric",
"score": 0.7230539917945862
},
{
"start": 260,
"end": 262,
"text": "Q6",
"label": "benchmark name",
"score": 0.6065879464149475
},
{
"start": 306,
"end": 320,
"text": "full... |
ytu-ce-cosmos/Turkish-Llama-8b-Instruct-v0.1-GGUF | ytu-ce-cosmos | 2024-12-03T18:01:34Z | 795 | 24 | null | [
"gguf",
"ggml",
"llama3",
"cosmosllama",
"turkish llama",
"tr",
"en",
"base_model:ytu-ce-cosmos/Turkish-Llama-8b-Instruct-v0.1",
"base_model:quantized:ytu-ce-cosmos/Turkish-Llama-8b-Instruct-v0.1",
"license:llama3",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2024-07-14T17:07:17Z | # CosmsoLLaMa GGUFs
## Objective
Due to the need for quantized models in real-time applications, we introduce our GGUF formatted models. These models are part of
GGML project with a hope to democratize the use of Large Models. Depending on the quantization type, there are 20+ models.
### Features
* All quantization ... | [] |
mradermacher/SvS-Qwen-Code-7B-i1-GGUF | mradermacher | 2025-12-11T15:42:41Z | 1,048 | 1 | transformers | [
"transformers",
"gguf",
"en",
"dataset:RLVR-SvS/Variational-DAPO",
"base_model:RLVR-SvS/SvS-Qwen-Code-7B",
"base_model:quantized:RLVR-SvS/SvS-Qwen-Code-7B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-11T13:10:48Z | ## 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": 617,
"end": 641,
"text": "SvS-Qwen-Code-7B-i1-GGUF",
"label": "benchmark name",
"score": 0.6820154786109924
}
] |
OpenGVLab/InternVL3_5-1B | OpenGVLab | 2025-08-29T17:57:08Z | 61,181 | 26 | transformers | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"internvl",
"custom_code",
"image-text-to-text",
"conversational",
"multilingual",
"dataset:OpenGVLab/MMPR-v1.2",
"dataset:OpenGVLab/MMPR-Tiny",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.1... | image-text-to-text | 2025-08-25T16:38:43Z | # InternVL3_5-1B
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggingface.co/pap... | [] |
prithivMLmods/granite-docling-258M-f32-GGUF | prithivMLmods | 2025-11-12T22:13:36Z | 164 | 3 | transformers | [
"transformers",
"gguf",
"ggml",
"llama.cpp",
"text-generation-inference",
"ocr",
"vlm",
"image-text-to-text",
"en",
"arxiv:2305.03393",
"arxiv:2501.17887",
"arxiv:2503.11576",
"base_model:ibm-granite/granite-docling-258M",
"base_model:quantized:ibm-granite/granite-docling-258M",
"license... | image-text-to-text | 2025-11-11T15:30:45Z | # **granite-docling-258M-f32-GGUF**
> [Granite-Docling-258M](https://huggingface.co/ibm-granite/granite-docling-258M) is an ultra-compact, open-source vision-language model developed by IBM Research specifically for high-fidelity end-to-end document conversion. With 258 million parameters, it builds upon the Idefics3 ... | [] |
Qwen/Qwen3-1.7B | Qwen | 2025-07-26T03:46:32Z | 6,806,823 | 430 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"arxiv:2505.09388",
"base_model:Qwen/Qwen3-1.7B-Base",
"base_model:finetune:Qwen/Qwen3-1.7B-Base",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-generation | 2025-04-27T03:41:05Z | # Qwen3-1.7B
<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 mod... | [] |
facebook/opt-2.7b | facebook | 2023-09-15T13:04:38Z | 20,075 | 87 | transformers | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"text-generation-inference",
"deploy:azure",
"region:us"
] | text-generation | 2022-05-11T08:26:30Z | # OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OPT... | [] |
priyadip/en-hi-transformer | priyadip | 2026-03-18T15:19:07Z | 147 | 1 | pytorch | [
"pytorch",
"custom_transformer",
"translation",
"transformer",
"seq2seq",
"english-to-hindi",
"from-scratch",
"ray-tune",
"optuna",
"en",
"hi",
"dataset:tatoeba",
"license:mit",
"model-index",
"region:us"
] | translation | 2026-03-18T14:31:35Z | # English → Hindi Transformer
A **from-scratch PyTorch encoder-decoder Transformer** for English → Hindi machine translation,
trained on a **raw [Tatoeba](https://tatoeba.org/en/downloads) EN-HI export**
(13 186 sentence pairs, including multiple Hindi translations per English sentence).
This repository provide... | [
{
"start": 382,
"end": 386,
"text": "BLEU",
"label": "evaluation metric",
"score": 0.8234811425209045
},
{
"start": 452,
"end": 460,
"text": "Baseline",
"label": "evaluation metric",
"score": 0.7660225629806519
},
{
"start": 703,
"end": 707,
"text": "BLEU"... |
inferencerlabs/MiniMax-M2.5-MLX-6.5bit | inferencerlabs | 2026-02-13T21:06:00Z | 283 | 1 | mlx | [
"mlx",
"safetensors",
"minimax_m2",
"quantized",
"text-generation",
"conversational",
"custom_code",
"en",
"base_model:MiniMaxAI/MiniMax-M2.5",
"base_model:quantized:MiniMaxAI/MiniMax-M2.5",
"6-bit",
"region:us"
] | text-generation | 2026-02-13T16:16:27Z | **See MiniMax-M2.5 MLX in action - [demonstration video](https://youtu.be/yWXK6zu_kGE)**
#### Tested on a M3 Ultra 512GB RAM using [Inferencer app v1.10](https://inferencer.com)
- Single inference ~39 tokens/s @ 1000 tokens
- Batched inference ~ total tokens/s across six inferences
- Memory usage: ~173 GiB
*q6.5bit q... | [
{
"start": 397,
"end": 407,
"text": "Perplexity",
"label": "evaluation metric",
"score": 0.7419922947883606
},
{
"start": 410,
"end": 424,
"text": "Token Accuracy",
"label": "evaluation metric",
"score": 0.8715240359306335
},
{
"start": 427,
"end": 444,
"t... |
mradermacher/GUI-Libra-4B-i1-GGUF | mradermacher | 2026-04-18T17:39:10Z | 291 | 1 | transformers | [
"transformers",
"gguf",
"VLM",
"GUI",
"agent",
"en",
"dataset:GUI-Libra/GUI-Libra-81K-RL",
"dataset:GUI-Libra/GUI-Libra-81K-SFT",
"base_model:GUI-Libra/GUI-Libra-4B",
"base_model:quantized:GUI-Libra/GUI-Libra-4B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"con... | null | 2026-03-01T07:39:56Z | ## 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/Llama-4-Scout-17B-16E-Instruct-GGUF | unsloth | 2025-06-17T15:28:28Z | 43,392 | 145 | transformers | [
"transformers",
"gguf",
"llama4",
"image-text-to-text",
"facebook",
"unsloth",
"meta",
"pytorch",
"llama",
"llama-4",
"ar",
"de",
"en",
"es",
"fr",
"hi",
"id",
"it",
"pt",
"th",
"tl",
"vi",
"arxiv:2204.05149",
"base_model:meta-llama/Llama-4-Scout-17B-16E-Instruct",
"b... | image-text-to-text | 2025-04-07T22:19:59Z | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/llama-4-67f19503d764b0f3a2a868d2">our collection</a> for versions of Llama 4 including 4-bit & 16-bit formats.</strong>
</p>
<p style="margin-bottom: 0; margin-top: 0;">
<em><a href="https://... | [] |
unsloth/Qwen-Image-Edit-2511-GGUF | unsloth | 2026-01-08T21:13:12Z | 105,604 | 413 | null | [
"gguf",
"quantized",
"unsloth",
"qwen",
"image-to-image",
"en",
"zh",
"arxiv:2508.02324",
"base_model:Qwen/Qwen-Image-Edit-2511",
"base_model:quantized:Qwen/Qwen-Image-Edit-2511",
"license:apache-2.0",
"region:us"
] | image-to-image | 2025-12-20T02:31:59Z | # Read our How to [Run Qwen-Image Guide!](https://unsloth.ai/docs/models/qwen-image-2512) 💜
This is a GGUF quantized version of [Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511). <br>
unsloth/Qwen-Image-Edit-2511-GGUF uses [Unsloth Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.... | [] |
shoumenchougou/RWKV7-G1e-7.2B-GGUF | shoumenchougou | 2026-03-19T10:17:00Z | 975 | 5 | null | [
"gguf",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-02T09:07:59Z | ## 1️⃣ What are G0 / G1 / G1a2 / G1b / G1c / G1d / G1e ?
The fields like G0 / G1a / G1b in RWKV model names indicate versions of the training data. In terms of data quality, the ranking is: **G1e > G1d > G1c > G1b > G1a2 > G1a > G1 > G0a2 > G0**.
The RWKV7-G1a model is an advanced version of RWKV7-G1 that was furthe... | [
{
"start": 335,
"end": 337,
"text": "1T",
"label": "evaluation metric",
"score": 0.6392597556114197
}
] |
mradermacher/Huihui-Qwen3-4B-abliterated-v2-i1-GGUF | mradermacher | 2025-07-11T00:46:26Z | 455 | 4 | transformers | [
"transformers",
"gguf",
"chat",
"abliterated",
"uncensored",
"en",
"base_model:huihui-ai/Huihui-Qwen3-4B-abliterated-v2",
"base_model:quantized:huihui-ai/Huihui-Qwen3-4B-abliterated-v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2025-06-19T13:00:12Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-Qwen3-4B-abliterated-v2
<!-- provided-files -->
***For a convenient overview and dow... | [] |
nvidia/AceReason-Nemotron-1.1-7B | nvidia | 2025-07-11T05:49:43Z | 4,760 | 58 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"nvidia",
"reasoning",
"math",
"code",
"supervised fine-tuning",
"reinforcement learning",
"pytorch",
"conversational",
"en",
"arxiv:2506.13284",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region... | text-generation | 2025-06-16T23:11:20Z | # AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy
<p align="center">
[](https://arxiv.org/abs/2506.13284)
[](https://huggingface.co/data... | [] |
mradermacher/Spatial-SSRL-Qwen3VL-4B-i1-GGUF | mradermacher | 2025-12-07T02:53:19Z | 112 | 2 | transformers | [
"transformers",
"gguf",
"multimodal",
"spatial",
"sptial understanding",
"self-supervised learning",
"en",
"dataset:internlm/Spatial-SSRL-81k",
"base_model:internlm/Spatial-SSRL-Qwen3VL-4B",
"base_model:quantized:internlm/Spatial-SSRL-Qwen3VL-4B",
"license:apache-2.0",
"endpoints_compatible",
... | null | 2025-11-25T00:31:06Z | ## 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_... | [
{
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"text": "Spatial-SSRL-Qwen3VL-4B",
"label": "benchmark name",
"score": 0.6048359274864197
},
{
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"end": 655,
"text": "Spatial-SSRL-Qwen3VL-4B-i1-GGUF",
"label": "benchmark name",
"score": 0.7522282004356384
},
{
"start": 729... |
Qwen/QwQ-32B | Qwen | 2025-03-11T12:15:48Z | 59,119 | 2,877 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2412.15115",
"base_model:Qwen/Qwen2.5-32B",
"base_model:finetune:Qwen/Qwen2.5-32B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azu... | text-generation | 2025-03-05T14:16:59Z | # QwQ-32B
<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>
## Introduction
QwQ is the reasoning model of the Qwen series. Compared ... | [
{
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"end": 9,
"text": "QwQ-32B",
"label": "benchmark name",
"score": 0.8744164705276489
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{
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"end": 267,
"text": "QwQ",
"label": "benchmark name",
"score": 0.799780547618866
},
{
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"end": 367,
"text": "QwQ",
"label":... |
inferencerlabs/GLM-5.1-MLX-4.8bit-INF | inferencerlabs | 2026-04-18T00:07:51Z | 4,768 | 6 | mlx | [
"mlx",
"safetensors",
"glm_moe_dsa",
"quantized",
"text-generation",
"conversational",
"en",
"base_model:zai-org/GLM-5.1",
"base_model:quantized:zai-org/GLM-5.1",
"region:us"
] | text-generation | 2026-04-13T07:04:04Z | **See GLM-5.1 MLX in action - [demonstration video](https://youtu.be/T-eBZIMc_sY)**
#### Tested on a M3 Ultra 512GB RAM using [Inferencer app](https://inferencer.com)
- Single inference ~14.1 tokens/s @ 1000 tokens (debug build)
- Batched inference ~20.4 total tokens/s across two inferences
- Memory usage: ~419.30 GiB... | [
{
"start": 664,
"end": 674,
"text": "Perplexity",
"label": "evaluation metric",
"score": 0.60249924659729
},
{
"start": 683,
"end": 697,
"text": "Token Accuracy",
"label": "evaluation metric",
"score": 0.8313795328140259
},
{
"start": 706,
"end": 723,
"tex... |
mradermacher/Huihui-granite-4.0-h-tiny-abliterated-i1-GGUF | mradermacher | 2025-12-06T03:48:56Z | 436 | 3 | transformers | [
"transformers",
"gguf",
"language",
"granite-4.0",
"abliterated",
"uncensored",
"en",
"base_model:huihui-ai/Huihui-granite-4.0-h-tiny-abliterated",
"base_model:quantized:huihui-ai/Huihui-granite-4.0-h-tiny-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
... | null | 2025-10-04T20:07:20Z | ## 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_... | [] |
NeuronUz/NeuronAI-Uzbek | NeuronUz | 2026-01-21T16:26:05Z | 134 | 4 | null | [
"safetensors",
"qwen3",
"uzbek",
"language-model",
"text-generation",
"nlp",
"central-asia",
"low-resource",
"tokenizer-optimization",
"conversational",
"uz",
"en",
"dataset:behbudiy/alpaca-cleaned-uz",
"dataset:NeuronUz/uzbek-spelling-mcq",
"base_model:Qwen/Qwen3-4B",
"base_model:fine... | text-generation | 2025-12-28T19:28:41Z | <div align="center">
# 🇺🇿 NeuronAI-Uzbek
### The Most Advanced Open-Source Language Model for Uzbek
[](https://huggingface.co/NeuronUz/NeuronAI-Uzbek)
[](https://opensource.org/l... | [
{
"start": 498,
"end": 513,
"text": "UzLiB Benchmark",
"label": "benchmark name",
"score": 0.7708054184913635
},
{
"start": 711,
"end": 730,
"text": "UzLiB Overall Score",
"label": "evaluation metric",
"score": 0.6807618141174316
},
{
"start": 831,
"end": 863,... |
microsoft/SportsBERT | microsoft | 2022-12-10T18:18:40Z | 312 | 28 | transformers | [
"transformers",
"pytorch",
"jax",
"bert",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | fill-mask | 2022-03-02T23:29:05Z | Pretraining large natural language processing models such as BERT, RoBERTa, etc are now state of the art models in natural language understanding and processing tasks. However, these models are trained on a general corpus of articles from the web or from repositories like quora, wikipedia, etc which contain articles of... | [] |
mradermacher/DeepSeek-R1-Distill-Qwen-1.5B-uncensored-GGUF | mradermacher | 2025-01-25T07:16:58Z | 2,427 | 22 | transformers | [
"transformers",
"gguf",
"en",
"base_model:thirdeyeai/DeepSeek-R1-Distill-Qwen-1.5B-uncensored",
"base_model:quantized:thirdeyeai/DeepSeek-R1-Distill-Qwen-1.5B-uncensored",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-01-23T15:20:59Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/thirdeyeai/DeepSeek-R1-Distill-Qwen-1.5B-uncensored
<!-- provided-files -->
weighted/imatrix quants are available at htt... | [] |
imageomics/bioclip-2.5-vith14 | imageomics | 2026-02-13T19:06:03Z | 2,396 | 5 | open_clip | [
"open_clip",
"safetensors",
"biology",
"CV",
"images",
"imageomics",
"clip",
"species-classification",
"biological visual task",
"multimodal",
"animals",
"plants",
"fungi",
"species",
"taxonomy",
"rare species",
"endangered species",
"evolutionary biology",
"knowledge-guided",
... | zero-shot-image-classification | 2026-02-10T01:57:02Z | <!--
Image with caption (jpg or png):
---
**Figure #.**
[Image of <>](
https://huggingface.co/imageomics/
<model-repo>/raw/main/<filepath>) <caption description>.
---
- ->
---
<!--
Notes on styling:
To render LaTex in you... | [] |
prithivMLmods/chandra-OCR-GGUF | prithivMLmods | 2025-11-14T18:42:45Z | 923 | 12 | transformers | [
"transformers",
"gguf",
"qwen3_vl",
"ggml",
"llama.cpp",
"text-generation-inference",
"ocr",
"vlm",
"markdown",
"html",
"json",
"image-text-to-text",
"en",
"base_model:datalab-to/chandra",
"base_model:quantized:datalab-to/chandra",
"license:openrail",
"endpoints_compatible",
"regio... | image-text-to-text | 2025-11-11T13:32:05Z | # **chandra-OCR-GGUF**
> [Chandra](https://huggingface.co/datalab-to/chandraa) is a highly accurate OCR model designed to convert images and PDFs into structured outputs such as markdown, HTML, and JSON while preserving detailed layout information. It supports over 40 languages and excels in handling complex document ... | [] |
mradermacher/Sayo-Qwen-8B-GGUF | mradermacher | 2026-03-06T12:01:32Z | 897 | 2 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Craleo/Sayo-Qwen-8B",
"base_model:quantized:Craleo/Sayo-Qwen-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-05T16:13:15Z | ## 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... | [] |
lmstudio-community/NVIDIA-Nemotron-3-Nano-30B-A3B-MLX-4bit | lmstudio-community | 2025-12-16T18:05:33Z | 179,887 | 2 | transformers | [
"transformers",
"safetensors",
"nvidia",
"pytorch",
"mlx",
"text-generation",
"conversational",
"en",
"es",
"fr",
"de",
"ja",
"it",
"dataset:nvidia/Nemotron-Pretraining-Code-v1",
"dataset:nvidia/Nemotron-CC-v2",
"dataset:nvidia/Nemotron-Pretraining-SFT-v1",
"dataset:nvidia/Nemotron-C... | text-generation | 2025-12-16T18:03:35Z | ## 💫 Community Model> NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 by nvidia
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [nvidia](https://huggingface.co/n... | [] |
onnx-community/Florence-2-base | onnx-community | 2025-05-08T19:39:44Z | 294 | 17 | transformers.js | [
"transformers.js",
"onnx",
"florence2",
"image-text-to-text",
"vision",
"text-generation",
"text2text-generation",
"image-to-text",
"base_model:microsoft/Florence-2-base",
"base_model:quantized:microsoft/Florence-2-base",
"license:mit",
"region:us"
] | image-text-to-text | 2024-06-21T23:25:59Z | https://huggingface.co/microsoft/Florence-2-base with ONNX weights to be compatible with Transformers.js.
## Usage (Transformers.js)
If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/trans... | [] |
mudler/NVIDIA-Nemotron-3-Super-120B-A12B-APEX-GGUF | mudler | 2026-04-27T14:00:04Z | 4,527 | 2 | null | [
"gguf",
"quantized",
"apex",
"moe",
"mixture-of-experts",
"nvidia",
"nemotron",
"mamba",
"hybrid",
"base_model:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
"base_model:quantized:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
"license:other",
"endpoints_compatible",
"region:us",
"conv... | null | 2026-04-05T23:06:23Z | <!-- apex-banner-v2 -->
<div style="background-color: #f59e0b; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
<h2 style="color: white; margin: 0 0 10px 0;">⚡ Each donation = another big MoE quantized</h2>
<p style="font-size: 18px; margin: 0 0 15px 0;">I host <b>25+ free APEX Mo... | [
{
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"end": 317,
"text": "APEX",
"label": "benchmark name",
"score": 0.6539493203163147
},
{
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"text": "APEX",
"label": "benchmark name",
"score": 0.6842774748802185
}
] |
MuXodious/gemma-3n-E4B-it-absolute-heresy-GGUF | MuXodious | 2026-01-21T17:34:33Z | 467 | 2 | transformers | [
"transformers",
"gguf",
"automatic-speech-recognition",
"automatic-speech-translation",
"audio-text-to-text",
"video-text-to-text",
"heretic",
"image-text-to-text",
"arxiv:1905.07830",
"arxiv:1905.10044",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1705.03551",
"arxiv:1911.01547",
"ar... | image-text-to-text | 2025-12-17T22:59:12Z | Gemma 3n E4B it finetune produced through a slightly modified version (to load and process the Gemma 3n model) of [P-E-W's heretic](https://github.com/p-e-w/heretic) (v1.1.0) abliteration engine with the [hybrid layer model support PR](https://github.com/p-e-w/heretic/pull/43) merged. This version of the heretic model ... | [
{
"start": 333,
"end": 352,
"text": "abliteration scores",
"label": "evaluation metric",
"score": 0.8136976957321167
},
{
"start": 1179,
"end": 1198,
"text": "Abliteration scores",
"label": "evaluation metric",
"score": 0.7635957598686218
},
{
"start": 1218,
"... |
timm/convnext_tiny.dinov3_lvd1689m | timm | 2025-09-18T20:14:24Z | 32,298 | 1 | timm | [
"timm",
"pytorch",
"safetensors",
"transformers",
"image-feature-extraction",
"arxiv:2508.10104",
"arxiv:2201.03545",
"license:other",
"region:us"
] | image-feature-extraction | 2025-09-11T18:09:43Z | # Model card for convnext_tiny.dinov3_lvd1689m
A DINOv3 ConvNeXt image feature model. Pretrained on LVD-1689M with self-supervised DINOv3 method, distilled from DINOv3 ViT-7B.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model Stats:**
- Params (M): 27.8
- GMACs: 4.5
- Activat... | [] |
mixedbread-ai/mxbai-rerank-large-v1 | mixedbread-ai | 2025-04-02T14:41:49Z | 60,406 | 141 | transformers | [
"transformers",
"onnx",
"safetensors",
"deberta-v2",
"text-classification",
"reranker",
"transformers.js",
"sentence-transformers",
"text-ranking",
"en",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-ranking | 2024-02-29T16:09:41Z | <br><br>
<p align="center">
<svg xmlns="http://www.w3.org/2000/svg" xml:space="preserve" viewBox="0 0 2020 1130" width="150" height="150" aria-hidden="true"><path fill="#e95a0f" d="M398.167 621.992c-1.387-20.362-4.092-40.739-3.851-61.081.355-30.085 6.873-59.139 21.253-85.976 10.487-19.573 24.09-36.822 40.662-51.515 16... | [] |
HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive | HauhauCS | 2026-04-05T19:00:05Z | 8,939 | 22 | null | [
"gguf",
"uncensored",
"glm4",
"moe",
"en",
"zh",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-24T17:03:08Z | # GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive
> **[Join the Discord](https://discord.gg/SZ5vacTXYf)** for updates, roadmaps, projects, or just to chat.
GLM-4.7 Flash uncensored by HauhauCS.
## About
No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without ... | [] |
mudler/MiniMax-M2.5-APEX-GGUF | mudler | 2026-04-27T13:59:57Z | 7,694 | 2 | null | [
"gguf",
"quantized",
"apex",
"moe",
"mixture-of-experts",
"minimax",
"base_model:MiniMaxAI/MiniMax-M2.5",
"base_model:quantized:MiniMaxAI/MiniMax-M2.5",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-02T21:08:10Z | <!-- apex-banner-v2 -->
<div style="background-color: #f59e0b; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
<h2 style="color: white; margin: 0 0 10px 0;">⚡ Each donation = another big MoE quantized</h2>
<p style="font-size: 18px; margin: 0 0 15px 0;">I host <b>25+ free APEX Mo... | [
{
"start": 313,
"end": 317,
"text": "APEX",
"label": "benchmark name",
"score": 0.6539493203163147
},
{
"start": 588,
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"text": "APEX",
"label": "benchmark name",
"score": 0.6842774748802185
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] |
Qwen/Qwen3-4B | Qwen | 2025-07-26T03:46:39Z | 6,329,184 | 576 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"arxiv:2309.00071",
"arxiv:2505.09388",
"base_model:Qwen/Qwen3-4B-Base",
"base_model:finetune:Qwen/Qwen3-4B-Base",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region... | text-generation | 2025-04-27T03:41:29Z | # Qwen3-4B
<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 model... | [] |
mradermacher/Logics-Parsing-v2-GGUF | mradermacher | 2026-02-14T09:04:46Z | 244 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Logics-MLLM/Logics-Parsing-v2",
"base_model:quantized:Logics-MLLM/Logics-Parsing-v2",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-14T08:46:45Z | ## 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... | [] |
mradermacher/Azure-Starlight-12B-i1-GGUF | mradermacher | 2026-02-24T02:00:13Z | 2,937 | 1 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"roleplay",
"en",
"base_model:Vortex5/Azure-Starlight-12B",
"base_model:quantized:Vortex5/Azure-Starlight-12B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-02-24T00:04:58Z | ## 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": 463,
"end": 482,
"text": "Azure-Starlight-12B",
"label": "benchmark name",
"score": 0.6365983486175537
},
{
"start": 619,
"end": 646,
"text": "Azure-Starlight-12B-i1-GGUF",
"label": "benchmark name",
"score": 0.7268652319908142
},
{
"start": 720,
"e... |
mradermacher/Qwen1.5-4B-Chat-heretic-i1-GGUF | mradermacher | 2026-01-14T08:51:50Z | 202 | 1 | transformers | [
"transformers",
"gguf",
"chat",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:addansee/Qwen1.5-4B-Chat-heretic",
"base_model:quantized:addansee/Qwen1.5-4B-Chat-heretic",
"license:other",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-14T07:14:08Z | ## 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": 464,
"end": 487,
"text": "Qwen1.5-4B-Chat-heretic",
"label": "benchmark name",
"score": 0.6431938409805298
},
{
"start": 624,
"end": 655,
"text": "Qwen1.5-4B-Chat-heretic-i1-GGUF",
"label": "benchmark name",
"score": 0.73231041431427
},
{
"start": 729,
... |
Flexan/DoodDood-TOMAGPT-GGUF | Flexan | 2026-02-24T08:09:03Z | 523 | 1 | null | [
"gguf",
"legal",
"hearsay",
"classification",
"grpo",
"reinforcement-learning",
"legalbench",
"lora",
"text-generation",
"dataset:DoodDood/HearsayGRPOTrainingData2",
"base_model:DoodDood/TOMAGPT",
"base_model:adapter:DoodDood/TOMAGPT",
"license:apache-2.0",
"model-index",
"endpoints_comp... | text-generation | 2026-02-23T15:51:42Z | # GGUF Files for TOMAGPT
These are the GGUF files for [DoodDood/TOMAGPT](https://huggingface.co/DoodDood/TOMAGPT).
## Downloads
| GGUF Link | Quantization | Description |
| ---- | ----- | ----------- |
| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q2_K.gguf) | Q2_K | L... | [] |
mradermacher/Nanbeige4-3B-Thinking-Ties-GGUF | mradermacher | 2025-12-22T10:24:48Z | 111 | 1 | transformers | [
"transformers",
"gguf",
"merge",
"mergekit",
"lazymergekit",
"Nanbeige/Nanbeige4-3B-Thinking-2511",
"C10X/Nanbeige4-3B-Thinking-2511-Claude-4.5-Opus-High-Reasoning-Distill-V2-heretic",
"arnomatic/Nanbeige4-3B-Thinking-2511-heretic",
"en",
"base_model:bunnycore/Nanbeige4-3B-Thinking-Ties",
"base_... | null | 2025-12-22T09:35:18Z | ## 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... | [] |
llm-semantic-router/lora_intent_classifier_bert-base-uncased_model | llm-semantic-router | 2025-11-10T18:26:36Z | 8,021 | 1 | candle | [
"candle",
"safetensors",
"bert",
"lora",
"semantic-router",
"intent-classification",
"text-classification",
"rust",
"en",
"base_model:google-bert/bert-base-uncased",
"base_model:adapter:google-bert/bert-base-uncased",
"license:apache-2.0",
"region:us"
] | text-classification | 2025-09-13T16:07:55Z | # lora_intent_classifier_bert-base-uncased_model
## Model Description
This is a LoRA (Low-Rank Adaptation) fine-tuned model based on **bert-base-uncased** for Intent Classification - Classifies text into categories like business, technology, science, etc..
This model is part of the [semantic-router](https://github.c... | [] |
openai/whisper-large-v3-turbo | openai | 2024-10-04T14:51:11Z | 4,993,604 | 2,865 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"en",
"zh",
"de",
"es",
"ru",
"ko",
"fr",
"ja",
"pt",
"tr",
"pl",
"ca",
"nl",
"ar",
"sv",
"it",
"id",
"hi",
"fi",
"vi",
"he",
"uk",
"el",
"ms",
"cs",
"ro",
"da",
"hu",
... | automatic-speech-recognition | 2024-10-01T07:39:28Z | # Whisper
Whisper is a state-of-the-art model for automatic speech recognition (ASR) and speech translation, proposed in the paper
[Robust Speech Recognition via Large-Scale Weak Supervision](https://huggingface.co/papers/2212.04356) by Alec Radford
et al. from OpenAI. Trained on >5M hours of labeled data, Whisper d... | [] |
bartowski/VibeStudio_MiniMax-M2-THRIFT-GGUF | bartowski | 2025-11-20T02:05:26Z | 3,053 | 8 | null | [
"gguf",
"moe",
"minimax",
"bfloat16",
"sglang",
"text-generation",
"dataset:nick007x/github-code-2025",
"dataset:tatsu-lab/alpaca",
"base_model:VibeStudio/MiniMax-M2-THRIFT",
"base_model:quantized:VibeStudio/MiniMax-M2-THRIFT",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",... | text-generation | 2025-11-19T16:54:44Z | ## Llamacpp imatrix Quantizations of MiniMax-M2-THRIFT by VibeStudio
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/b7049">b7049</a> for quantization.
Original model: https://huggingface.co/VibeStudio/MiniMax-M2-THRIFT
All quan... | [
{
"start": 37,
"end": 54,
"text": "MiniMax-M2-THRIFT",
"label": "benchmark name",
"score": 0.647960901260376
},
{
"start": 293,
"end": 310,
"text": "MiniMax-M2-THRIFT",
"label": "benchmark name",
"score": 0.6219571232795715
}
] |
Alibaba-DAMO-Academy/RynnBrain-Nav-8B | Alibaba-DAMO-Academy | 2026-04-14T07:07:59Z | 1,980 | 13 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"robotics",
"embodied-ai",
"egocentric",
"spatiotemporal",
"vision-language-model",
"video-understanding",
"grounding",
"planning",
"navigation",
"ocr",
"video-text-to-text",
"custom_code",
"conversational",
"en",
"... | image-text-to-text | 2026-01-28T08:55:14Z | <p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/66974212a9e7257fc37798dc/8eIGdvaZEuZKTcsjIAXXK.png" width="350" style="margin-bottom: 0.2;"/>
<p
<h2 align="center"><a href="https://github.com/alibaba-damo-academy/RynnBrain">RynnBrain: Open Embodied Foundation Models</a></h3>
<h5 a... | [] |
Ayodele01/gemma-4-E4B-Gemini-3.1-Pro-Reasoning-Distill-GGUF | Ayodele01 | 2026-04-05T06:17:58Z | 329 | 2 | gguf | [
"gguf",
"gemma",
"gemma-4",
"reasoning",
"chain-of-thought",
"llama-cpp",
"fine-tuned",
"text-generation",
"en",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-04-03T22:15:43Z | # Gemma-4 E4B Gemini 3.1 Pro Reasoning Distill - GGUF
GGUF quantized versions of [Ayodele01/gemma-4-E4B-Gemini-3.1-Pro-Reasoning-Distill](https://huggingface.co/Ayodele01/gemma-4-E4B-Gemini-3.1-Pro-Reasoning-Distill).
## Model Description
This is Google's Gemma-4 4B (E4B) instruction-tuned model, fine-tuned on Gemin... | [] |
ricdomolm/lawma-8b | ricdomolm | 2025-02-25T15:57:06Z | 121 | 15 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"legal",
"conversational",
"en",
"dataset:ricdomolm/lawma-all-tasks",
"arxiv:2407.16615",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-22T10:05:53Z | # Lawma 8B
Lawma 8B is a fine-tune of Llama 3 8B Instruct on 260 legal classification tasks derived from [Supreme Court](http://scdb.wustl.edu/data.php) and [Songer Court of Appeals](www.songerproject.org/us-courts-of-appeals-databases.html) databases. Lawma was fine-tuned on over 500k task examples, totalling 2B toke... | [
{
"start": 358,
"end": 363,
"text": "GPT-4",
"label": "benchmark name",
"score": 0.7194061279296875
},
{
"start": 620,
"end": 648,
"text": "mean classification accuracy",
"label": "evaluation metric",
"score": 0.6119371652603149
},
{
"start": 1109,
"end": 1113... |
mradermacher/Qwen3-8B-finance-V1.0.1-Merged-V2-GGUF | mradermacher | 2026-01-03T01:36:26Z | 197 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3",
"en",
"dataset:RinKana/finance-reasoning-synthetic",
"base_model:RinKana/Qwen3-8B-finance-V1.0.1-Merged-V2",
"base_model:quantized:RinKana/Qwen3-8B-finance-V1.0.1-Merged-V2",
"license:apache-2.0",
"endpoints_compatible",
... | null | 2026-01-02T17:00:46Z | ## 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... | [] |
bartowski/mistralai_Ministral-3-14B-Instruct-2512-GGUF | bartowski | 2025-12-19T19:44:24Z | 2,760 | 2 | null | [
"gguf",
"mistral-common",
"image-text-to-text",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"base_model:mistralai/Ministral-3-14B-Instruct-2512-BF16",
"base_model:quantized:mistralai/Ministral-3-14B-Instruct-2512-BF16",
"license:apache-2.0",
"region:us",
"co... | image-text-to-text | 2025-12-02T15:46:49Z | ## Llamacpp imatrix Quantizations of Ministral-3-14B-Instruct-2512 by mistralai
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/b7229">b7229</a> for quantization.
Original model: https://huggingface.co/mistralai/Ministral-3-14B-I... | [] |
foduucom/thermal-image-object-detection | foduucom | 2023-08-28T07:12:05Z | 128 | 22 | ultralytics | [
"ultralytics",
"tensorboard",
"v8",
"ultralyticsplus",
"yolov8",
"ultralyticsYOLOv8s Table Detection",
"yolo",
"computer-vision",
"object-detection",
"pytorch",
"en",
"model-index",
"region:us"
] | object-detection | 2023-08-08T10:10:21Z | <div align="center">
<img width="640" alt="foduucom/thermal-image-object-detection" src="https://huggingface.co/foduucom/thermal-image-object-detection/resolve/main/image.jpg">
</div>
# Model Card for YOLOv8 object detection in thermal image
## Note
This model is specially design for thermal image object detectio... | [] |
mradermacher/Qwen3.5-2B-Polaris-HighIQ-Thinking-Compact-GGUF | mradermacher | 2026-03-05T10:40:50Z | 1,667 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"instruct",
"finetune",
"thinking",
"reasoning",
"en",
"dataset:TeichAI/polaris-alpha-1000x",
"base_model:DavidAU/Qwen3.5-2B-Polaris-HighIQ-Thinking-Compact",
"base_model:quantized:DavidAU/Qwen3.5-2B-Polaris-HighIQ-Thinking-Compact",
"license:apache-2.0",
"... | null | 2026-03-05T09:27:28Z | ## 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/Ministral-3-14B-Reasoning-2512-GGUF | mradermacher | 2025-12-02T18:37:35Z | 157 | 1 | transformers | [
"transformers",
"gguf",
"mistral-common",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"base_model:mistralai/Ministral-3-14B-Reasoning-2512",
"base_model:quantized:mistralai/Ministral-3-14B-Reasoning-2512",
"license:apache-2.0",
"endpoints_compatible",
"regio... | null | 2025-12-02T17:10:40Z | ## 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/FinR1-llama-8b-multi-language-thinking-GGUF | mradermacher | 2025-10-31T21:25:54Z | 1,670 | 1 | transformers | [
"transformers",
"gguf",
"finance",
"fine-tuning",
"conversational-ai",
"quantitative-reasoning",
"multilingual",
"llama",
"reasoning-traces",
"structured-thinking",
"lightweight-llm",
"rag",
"en",
"zh",
"ar",
"uz",
"ja",
"es",
"dataset:Josephgflowers/Finance-Instruct-500k",
"da... | null | 2025-10-31T00:11:57Z | ## 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: -->
static q... | [] |
MuXodious/GLM-4.7-Flash-absolute-heresy | MuXodious | 2026-02-14T15:55:37Z | 353 | 6 | transformers | [
"transformers",
"safetensors",
"glm4_moe_lite",
"text-generation",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"en",
"zh",
"arxiv:2508.06471",
"base_model:zai-org/GLM-4.7-Flash",
"base_model:finetune:zai-org/GLM-4.7-Flash",
"license:mit",
"endpoints_compatib... | text-generation | 2026-02-14T15:22:27Z | This is a **GLM-4.7-Flash** fine-tune, produced through P-E-W's [Heretic](https://github.com/p-e-w/heretic) (v1.2.0) abliteration engine with [Magnitude-Preserving Orthogonal Ablation](https://github.com/p-e-w/heretic/pull/52) enabled.
**Note:** The model was generated with Transformers v5.
---
<img src="https://img.... | [] |
mradermacher/HyperNova-60B-GGUF | mradermacher | 2026-01-04T09:13:47Z | 129 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:MultiverseComputingCAI/HyperNova-60B",
"base_model:quantized:MultiverseComputingCAI/HyperNova-60B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-04T01:22:22Z | ## 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": 525,
"end": 543,
"text": "HyperNova-60B-GGUF",
"label": "benchmark name",
"score": 0.667706310749054
}
] |
bartowski/huihui-ai_Qwen3-14B-abliterated-GGUF | bartowski | 2025-05-06T07:59:50Z | 4,901 | 13 | null | [
"gguf",
"chat",
"abliterated",
"uncensored",
"text-generation",
"base_model:huihui-ai/Qwen3-14B-abliterated",
"base_model:quantized:huihui-ai/Qwen3-14B-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-05-06T05:21:32Z | ## Llamacpp imatrix Quantizations of Qwen3-14B-abliterated by huihui-ai
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b5284">b5284</a> for quantization.
Original model: https://huggingface.co/huihui-ai/Qwen3-14B-abliterated
... | [] |
KlingTeam/VidEmo-3B | KlingTeam | 2025-12-07T00:02:58Z | 125 | 3 | null | [
"safetensors",
"qwen2_5_vl",
"video-text-to-text",
"en",
"dataset:KlingTeam/Emo-CFG",
"arxiv:2511.02712",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"license:apache-2.0",
"region:us"
] | video-text-to-text | 2025-12-01T09:38:56Z | <div align=center>
<img src="assets/logo.png" width=15%>
<h1>VidEmo: Affective-Tree Reasoning for Emotion-Centric Video Foundation Models</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://zzcheng.top/" target="_blank">Zhicheng Zhang</a><sup>1,†</sup>,
</span>... | [] |
mradermacher/Gemma3-27B-it-vl-Polaris-HI16-Heretic-Uncensored-INSTRUCT-i1-GGUF | mradermacher | 2026-02-28T15:00:10Z | 6,532 | 1 | transformers | [
"transformers",
"gguf",
"gemma3",
"tuned instruct",
"intelligence fine tuning",
"heretic",
"uncensored",
"abliterated",
"finetune",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fi... | null | 2026-02-28T13:18:53Z | ## 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_... | [] |
openbmb/MiniCPM-SALA | openbmb | 2026-04-03T02:20:56Z | 1,353 | 496 | transformers | [
"transformers",
"safetensors",
"minicpm_sala",
"text-generation",
"conversational",
"custom_code",
"zh",
"en",
"arxiv:2509.24663",
"arxiv:2601.22156",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-11T07:03:05Z | <div align="center">
<img src="https://github.com/OpenBMB/MiniCPM/blob/main/assets/minicpm_logo.png?raw=true" width="500em" ></img>
</div>
<p align="center">
<a href="https://github.com/OpenBMB/MiniCPM/" target="_blank">GitHub Repo</a> |
<a href="https://github.com/OpenBMB/MiniCPM/blob/main/docs/MiniCPM_SALA.pdf" tar... | [] |
nvidia/GR00T-N1.7-SimplerEnv-Bridge | nvidia | 2026-04-20T23:07:55Z | 233 | 1 | null | [
"safetensors",
"Gr00tN1d7",
"robotics",
"arxiv:2503.14734",
"region:us"
] | robotics | 2026-03-17T16:45:55Z | <div align="center">
<a href="https://github.com/NVIDIA/Isaac-GR00T">
<img src="https://cdn-uploads.huggingface.co/production/uploads/67b8da81d01134f89899b4a7/8bFQa2ZIGCsOQQ2ho2N_U.png">
</a>
<div align="center">
<a href="https://github.com/NVIDIA/Isaac-GR00T">
<img src="https://img.shields.io/badge/Git... | [] |
unsloth/Phi-4-mini-instruct-GGUF | unsloth | 2025-03-03T00:53:59Z | 23,624 | 85 | transformers | [
"transformers",
"gguf",
"phi3",
"text-generation",
"phi",
"phi4",
"unsloth",
"nlp",
"code",
"microsoft",
"math",
"chat",
"conversational",
"custom_code",
"multilingual",
"base_model:microsoft/Phi-4-mini-instruct",
"base_model:quantized:microsoft/Phi-4-mini-instruct",
"license:mit",... | text-generation | 2025-02-28T22:22:06Z | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>This is Phi-4-mini-instruct with our BUG FIXES. <br> See <a href="https://huggingface.co/collections/unsloth/phi-4-all-versions-677eecf93784e61afe762afa">our collection</a> for versions of Phi-4 with our bug fixes including GGUF & 4-bit formats.</strong... | [] |
mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-i1-GGUF | mradermacher | 2025-12-21T22:16:26Z | 239 | 3 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"esper",
"shining-valiant",
"valiant",
"mistral3",
"mistral",
"mistral-common",
"ministral-3-14b",
"ministral",
"reasoning",
"code",
"code-reasoning",
"code-instruct",
"python",
"javascript",
"dev-ops",
"jenkins",
"terraform",
"s... | null | 2025-12-21T12:17:36Z | ## 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_... | [] |
jinaai/jina-reranker-v3-GGUF | jinaai | 2025-10-04T21:40:54Z | 1,856 | 14 | llama.cpp | [
"llama.cpp",
"gguf",
"reranker",
"qwen3",
"llama-cpp",
"text-ranking",
"multilingual",
"arxiv:2509.25085",
"base_model:jinaai/jina-reranker-v3",
"base_model:quantized:jinaai/jina-reranker-v3",
"license:cc-by-nc-4.0",
"region:eu"
] | text-ranking | 2025-10-04T20:40:09Z | # jina-reranker-v3-GGUF
GGUF quantizations of [jina-reranker-v3](https://huggingface.co/jinaai/jina-reranker-v3) using llama.cpp. A 0.6B parameter multilingual listwise reranker quantized for efficient inference.
## Requirements
- Python 3.8+
- llama.cpp binaries (`llama-embedding` and `llama-tokenize`)
- Hanxiao's ... | [] |
prithivMLmods/QIE-2511-Outfit-Design-Layout | prithivMLmods | 2026-01-27T12:16:12Z | 2,689 | 4 | diffusers | [
"diffusers",
"lora",
"art",
"design-layout",
"image-to-image",
"en",
"base_model:Qwen/Qwen-Image-Edit-2511",
"base_model:adapter:Qwen/Qwen-Image-Edit-2511",
"doi:10.57967/hf/7655",
"license:apache-2.0",
"region:us"
] | image-to-image | 2026-01-26T06:25:14Z | 
# **QIE-2511-Outfit-Design-Layout**
> **QIE-2511-Outfit-Design-Layout** is an adapter LoRA devel... | [] |
nvidia/Llama-3.1-Nemotron-70B-Instruct-HF | nvidia | 2025-04-13T04:12:19Z | 10,325 | 2,065 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"nvidia",
"llama3.1",
"conversational",
"en",
"dataset:nvidia/HelpSteer2",
"arxiv:2410.01257",
"arxiv:2405.01481",
"arxiv:2406.08673",
"base_model:meta-llama/Llama-3.1-70B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-70B-In... | text-generation | 2024-10-12T02:37:13Z | # Model Overview
## Description:
Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries.
This model reaches [Arena Hard](https://github.com/lmarena/arena-hard-auto) of 85.0, [AlpacaEval 2 LC](https://tatsu-lab.github.io/al... | [
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mudler/gemma-4-26B-A4B-it-Claude-Opus-Distill-APEX-GGUF | mudler | 2026-04-27T14:00:50Z | 20,971 | 15 | null | [
"gguf",
"quantized",
"apex",
"moe",
"mixture-of-experts",
"gemma4",
"claude-distilled",
"vlm",
"vision",
"base_model:TeichAI/gemma-4-26B-A4B-it-Claude-Opus-Distill",
"base_model:quantized:TeichAI/gemma-4-26B-A4B-it-Claude-Opus-Distill",
"license:gemma",
"endpoints_compatible",
"region:us",... | null | 2026-04-05T02:57:32Z | <!-- apex-banner-v2 -->
<div style="background-color: #f59e0b; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
<h2 style="color: white; margin: 0 0 10px 0;">⚡ Each donation = another big MoE quantized</h2>
<p style="font-size: 18px; margin: 0 0 15px 0;">I host <b>25+ free APEX Mo... | [
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mradermacher/H4rmoniousQwen-7b-GGUF | mradermacher | 2025-12-27T15:16:06Z | 119 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen2",
"en",
"base_model:neovalle/H4rmoniousQwen-7b",
"base_model:quantized:neovalle/H4rmoniousQwen-7b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-27T13:20:47Z | ## 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... | [] |
unsloth/Kimi-K2-Instruct-0905-GGUF | unsloth | 2025-09-06T07:20:31Z | 541 | 52 | transformers | [
"transformers",
"gguf",
"unsloth",
"base_model:moonshotai/Kimi-K2-Instruct-0905",
"base_model:quantized:moonshotai/Kimi-K2-Instruct-0905",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-05T06:07:00Z | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>Learn how to run Kimi-K2 Dynamic GGUFs - <a href="https://docs.unsloth.ai/basics/kimi-k2">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 Dy... | [] |
ICT-TIME-and-Querit/BOOM_4B_v1 | ICT-TIME-and-Querit | 2026-04-13T02:53:16Z | 114 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"mergekit",
"merge",
"arxiv:2602.05787",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-30T07:24:17Z | # Model Overview
Model Type: Text Embedding
Number of Parameters: 4B
Context Length: 32k
Adapted from Qwen/Qwen3-4B
Pooling: Last token
---
<div align="center">
<h1>
Robust Training for General Text Embeddings via Bagging-Based Model Merging
</h1>
</div>
<p align="center">
📖 <a href="... | [
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mradermacher/MediQwen-Reasoning-14B-i1-GGUF | mradermacher | 2025-12-04T13:03:11Z | 1,500 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3",
"en",
"base_model:justinj92/MediQwen-Reasoning-14B",
"base_model:quantized:justinj92/MediQwen-Reasoning-14B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-11-29T11:29:05Z | ## 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_... | [
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pyannote/wespeaker-voxceleb-resnet34-LM | pyannote | 2024-05-10T19:36:24Z | 13,538,198 | 107 | pyannote-audio | [
"pyannote-audio",
"pytorch",
"pyannote",
"pyannote-audio-model",
"wespeaker",
"audio",
"voice",
"speech",
"speaker",
"speaker-recognition",
"speaker-verification",
"speaker-identification",
"speaker-embedding",
"dataset:voxceleb",
"license:cc-by-4.0",
"region:us"
] | null | 2023-11-13T15:32:31Z | Using this open-source model in production?
Consider switching to [pyannoteAI](https://www.pyannote.ai) for better and faster options.
# 🎹 Wrapper around wespeaker-voxceleb-resnet34-LM
This model requires `pyannote.audio` version 3.1 or higher.
This is a wrapper around [WeSpeaker](https://github.com/wenet-e2e/wes... | [] |
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