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 |
|---|---|---|---|---|---|---|---|---|---|---|
unsloth/DeepSeek-R1-Distill-Llama-70B-GGUF | unsloth | 2025-05-10T20:16:36Z | 25,205 | 108 | transformers | [
"transformers",
"gguf",
"llama",
"text-generation",
"deepseek",
"unsloth",
"llama-3",
"meta",
"en",
"arxiv:2501.12948",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"license:llama3.3",
"endpoints_compatible",
"r... | text-generation | 2025-01-20T14:59:13Z | ## ***See [our collection](https://huggingface.co/collections/unsloth/deepseek-r1-all-versions-678e1c48f5d2fce87892ace5) for versions of Deepseek-R1 including GGUF and original formats.***
### Instructions to run this model in llama.cpp:
Or you can view more detailed instructions here: [unsloth.ai/blog/deepseek-r1](ht... | [] |
JetLM/SDAR-8B-Chat | JetLM | 2025-10-21T01:59:06Z | 3,666 | 3 | transformers | [
"transformers",
"safetensors",
"sdar",
"text-generation",
"conversational",
"custom_code",
"arxiv:2510.06303",
"arxiv:2505.09388",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-08-11T11:40:53Z | # SDAR
<div align="center">
<img src="https://raw.githubusercontent.com/JetAstra/SDAR/main/assets/SDAR_doc_head.png">
<div> </div>
[Arxiv](https://arxiv.org/abs/2510.06303) • [💻Github Repo](https://github.com/JetAstra/SDAR) • [🤗Model Collections](https://huggingface.co/collections/JetLM/sdar-689b1b6d392a4eeb... | [
{
"start": 753,
"end": 757,
"text": "SDAR",
"label": "benchmark name",
"score": 0.6389777064323425
},
{
"start": 1289,
"end": 1317,
"text": "Superior Learning Efficiency",
"label": "evaluation metric",
"score": 0.7101485133171082
}
] |
OpenMuQ/MuQ-large-msd-iter | OpenMuQ | 2025-08-15T10:45:28Z | 286,453 | 20 | null | [
"pytorch",
"safetensors",
"music",
"audio-classification",
"en",
"zh",
"arxiv:2501.01108",
"license:cc-by-nc-4.0",
"region:us"
] | audio-classification | 2024-12-17T07:29:00Z | # MuQ & MuQ-MuLan
<div>
<a href='#'><img alt="Static Badge" src="https://img.shields.io/badge/Python-3.8%2B-blue?logo=python&logoColor=white"></a>
<a href='https://arxiv.org/abs/2501.01108'><img alt="Static Badge" src="https://img.shields.io/badge/arXiv-2501.01108-%23b31b1b?logo=arxiv&link=https%3A%2F%2Farxiv.org%... | [] |
amd/DeepSeek-R1-MXFP4 | amd | 2026-04-13T16:42:07Z | 85,893 | 5 | null | [
"safetensors",
"deepseek_v3",
"custom_code",
"base_model:deepseek-ai/DeepSeek-R1",
"base_model:quantized:deepseek-ai/DeepSeek-R1",
"license:mit",
"8-bit",
"quark",
"region:us"
] | null | 2025-05-21T07:55:49Z | # Model Overview
- **Model Architecture:** DeepSeek-R1
- **Input:** Text
- **Output:** Text
- **Supported Hardware Microarchitecture:** AMD MI350/MI355
- **ROCm**: 7.0
- **PyTorch**: 2.8.0
- **Transformers**: 4.53.0
- **Operating System(s):** Linux
- **Inference Engine:** [SGLang](https://docs.sglang.ai/)
- **Mode... | [] |
typhoon-ai/typhoon-translate1.5-4b | typhoon-ai | 2025-11-10T11:49:59Z | 241 | 3 | null | [
"safetensors",
"qwen3",
"th",
"en",
"arxiv:2412.13702",
"license:apache-2.0",
"region:us"
] | null | 2025-10-26T17:31:23Z | **Typhoon Translate 1.5**
**Typhoon-Translate v1.5** is a lightweight, 4-billion-parameter language model designed specifically for **controllable**, **high-quality** Thai ↔ English translation—right from your local device.
Building on feedback from Typhoon-Translate v1, version 1.5 addresses the controllability issu... | [] |
bartowski/google_gemma-3-4b-it-GGUF | bartowski | 2025-03-22T20:18:26Z | 48,304 | 32 | null | [
"gguf",
"image-text-to-text",
"base_model:google/gemma-3-4b-it",
"base_model:quantized:google/gemma-3-4b-it",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2025-03-12T13:11:48Z | ## Llamacpp imatrix Quantizations of gemma-3-4b-it by google
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b4877">b4877</a> for quantization.
Original model: https://huggingface.co/google/gemma-3-4b-it
All quants made using ... | [] |
Salesforce/GTA1-32B | Salesforce | 2025-10-03T23:22:40Z | 333 | 6 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"VLM",
"Computer-Use-Agent",
"OS-Agent",
"GUI",
"Grounding",
"conversational",
"en",
"arxiv:2507.05791",
"license:mit",
"eval-results",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-09-25T06:08:58Z | # Introduction
Reinforcement learning (RL) (e.g., GRPO) helps with grounding because of its inherent objective alignment—rewarding successful clicks—rather than encouraging long textual Chain-of-Thought (CoT) reasoning. Unlike approaches that rely heavily on verbose CoT reasoning, GRPO directly incentivizes actionable... | [
{
"start": 51,
"end": 55,
"text": "GRPO",
"label": "benchmark name",
"score": 0.6210203170776367
},
{
"start": 493,
"end": 497,
"text": "GRPO",
"label": "benchmark name",
"score": 0.6061347723007202
},
{
"start": 502,
"end": 523,
"text": "Grounding Perform... |
unsloth/granite-4.0-h-350m-GGUF | unsloth | 2025-10-28T11:23:44Z | 1,096 | 9 | transformers | [
"transformers",
"gguf",
"language",
"unsloth",
"granite-4.0",
"arxiv:0000.00000",
"base_model:ibm-granite/granite-4.0-h-350m",
"base_model:quantized:ibm-granite/granite-4.0-h-350m",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-28T11:02:39Z | <div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
<div style="display: flex; gap: 5px; align-items: center; ">
<a href="https://github.com/u... | [] |
bowphs/SPhilBerta | bowphs | 2025-09-18T09:08:53Z | 411 | 10 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"safetensors",
"roberta",
"sentence-similarity",
"multilingual",
"grc",
"en",
"la",
"arxiv:2308.12008",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | sentence-similarity | 2023-08-24T12:32:27Z | # SPhilBerta
The paper [Exploring Language Models for Classical Philology](https://aclanthology.org/2023.acl-long.846/) is the first effort to systematically provide state-of-the-art language models for Classical Philology. Using PhilBERTa as a foundation, we introduce SPhilBERTa, a Sentence Transformer model to ident... | [] |
mradermacher/Qwen3.5-27B-Writer-GGUF | mradermacher | 2026-03-08T18:43:43Z | 3,090 | 2 | transformers | [
"transformers",
"gguf",
"en",
"dataset:ConicCat/Gutenberg-SFT",
"dataset:PJMixers-Dev/C2-Logs-Sonnet-4.5-all",
"dataset:ConicCat/AntiRep",
"dataset:ConicCat/Condor-SFT-Filtered",
"base_model:ConicCat/Qwen3.5-27B-Writer",
"base_model:quantized:ConicCat/Qwen3.5-27B-Writer",
"license:apache-2.0",
"... | null | 2026-03-07T21:22:20Z | ## 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... | [
{
"start": 1179,
"end": 1183,
"text": "Q2_K",
"label": "benchmark name",
"score": 0.6037711501121521
}
] |
embedl/Cosmos-Reason2-2B-NVFP4A16 | embedl | 2026-03-02T13:03:15Z | 261 | 1 | cosmos | [
"cosmos",
"safetensors",
"qwen3_vl",
"nvidia",
"cosmos-reason2",
"multimodal",
"vlm",
"quantized",
"edge",
"llmcompressor",
"NVFP4",
"image-text-to-text",
"conversational",
"base_model:nvidia/Cosmos-Reason2-2B",
"base_model:quantized:nvidia/Cosmos-Reason2-2B",
"license:other",
"compr... | image-text-to-text | 2026-02-23T12:52:49Z | # Cosmos-Reason2-2B-NVFP4A16
**Optimized version of [nvidia/Cosmos-Reason2-2B](https://huggingface.co/nvidia/Cosmos-Reason2-2B) using
Quantization.** Optimized for reduced GPU memory usage and improved inference efficiency while
maintaining high-quality multimodal reasoning performance.
This model was created by quan... | [
{
"start": 347,
"end": 358,
"text": "FP4 weights",
"label": "evaluation metric",
"score": 0.6447626352310181
}
] |
mradermacher/Qwen2.5-Math-Coder-Distill-Phi-2-4.4K-MixMathCode-GGUF | mradermacher | 2025-09-30T12:47:22Z | 129 | 2 | transformers | [
"transformers",
"gguf",
"phi-2",
"code-generation",
"math",
"reasoning",
"gsm8k",
"distilled",
"code",
"en",
"dataset:google-research-datasets/mbpp",
"dataset:gsm8k",
"dataset:OpenCoder-LLM/opc-sft-stage2",
"dataset:meta-math/MetaMathQA",
"base_model:DeryFerd/Qwen2.5-Math-Coder-Distill-P... | null | 2025-09-30T12:25:47Z | ## 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... | [] |
kyutai/tts-1.6b-en_fr | kyutai | 2025-09-11T08:50:45Z | 33,604 | 373 | moshi | [
"moshi",
"tts",
"audio",
"text-to-speech",
"en",
"fr",
"arxiv:2509.08753",
"arxiv:2410.00037",
"arxiv:2502.03382",
"license:cc-by-4.0",
"region:us"
] | text-to-speech | 2025-06-30T09:12:42Z | # Model Card for Kyutai TTS
See also the [pre-print research paper](https://arxiv.org/abs/2509.08753),
the [project page](https://kyutai.org/next/tts),
the [Colab example](https://colab.research.google.com/github/kyutai-labs/delayed-streams-modeling/blob/main/tts_pytorch.ipynb),
the [GitHub repository](https://github... | [] |
nothingiisreal/MN-12B-Celeste-V1.9 | nothingiisreal | 2024-08-24T00:51:29Z | 419 | 157 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"en",
"dataset:nothingiisreal/c2-logs-cleaned",
"dataset:kalomaze/Opus_Instruct_25k",
"dataset:nothingiisreal/Reddit-Dirty-And-WritingPrompts",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatibl... | text-generation | 2024-07-31T04:55:12Z | <style>
h1, h2, h3, h4, h5, h6 {
line-height: normal;
margin-bottom: 0.5em;
}
h1 {
font-size: 3em;
}
h2 {
font-size: 1.6em;
}
p, ul, ol, strong, summary {
font-size: 1.1em;
}
.line-spaceless {
line-height: 1;
margin: 0;
padding: 0;
}
.half-space {
line-height: 0... | [] |
baa-ai/Qwen3.6-27B-RAM-16GB-MLX | baa-ai | 2026-04-27T04:59:46Z | 759 | 3 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"quantized",
"mixed-precision",
"qwen",
"qwen3",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen3.6-27B",
"base_model:quantized:Qwen/Qwen3.6-27B",
"license:apache-2.0",
"4-bit",
"region:us"
] | text-generation | 2026-04-23T09:45:34Z | # Qwen3.6-27B — 16GB (MLX)
Mixed-precision MLX build of [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B), prepared by [baa.ai](https://baa.ai).
Built at the predicted local (capability) operating point.
## Metrics
| Metric | Value |
|---|---|
| **In-memory footprint** | **~16 GiB** |
| Size on disk | 18.... | [
{
"start": 2,
"end": 13,
"text": "Qwen3.6-27B",
"label": "benchmark name",
"score": 0.6393934488296509
},
{
"start": 429,
"end": 445,
"text": "Qwen/Qwen3.6-27B",
"label": "benchmark name",
"score": 0.6997396349906921
},
{
"start": 803,
"end": 820,
"text": ... |
apple/DiffuCoder-7B-cpGRPO | apple | 2025-12-08T04:58:59Z | 1,738 | 317 | null | [
"safetensors",
"Dream",
"code",
"text-diffusion-model",
"diffusion large language model",
"custom_code",
"arxiv:2506.20639",
"base_model:apple/DiffuCoder-7B-Instruct",
"base_model:finetune:apple/DiffuCoder-7B-Instruct",
"license:apple-amlr",
"region:us"
] | null | 2025-07-01T21:50:46Z | ### DiffuCoder-7B-cpGRPO
The DiffuCoder-7B-cpGRPO variant further refines DiffuCoder-Instruct with reinforcement learning via Coupled-GRPO.
Training recipe:
- Initialized from DiffuCoder-7B-Instruct, post-training with coupled-GRPO on 21K code data (1 epoch).
- coupled-GRPO significantly improves DiffuCoder's perfor... | [
{
"start": 367,
"end": 375,
"text": "EvalPlus",
"label": "benchmark name",
"score": 0.637442409992218
}
] |
OpenMOSE/Qwen3.5-REAP-212B-A17B | OpenMOSE | 2026-02-26T05:14:02Z | 266 | 14 | null | [
"safetensors",
"qwen3_5_moe",
"base_model:Qwen/Qwen3.5-397B-A17B",
"base_model:finetune:Qwen/Qwen3.5-397B-A17B",
"license:apache-2.0",
"region:us"
] | null | 2026-02-22T21:11:08Z | ## OpenMOSE/Qwen3.5-REAP-212B-A17B
Vision–Language MoE model created by applying **Router-weighted Expert Activation Pruning (REAP)** to **Qwen3.5-397B-A17B**.
Now, 35% Version also available :) more strong, more stable
https://huggingface.co/OpenMOSE/Qwen3.5-REAP-262B-A17B-GGUF
---
### 1. Model Summary
* **Base... | [] |
mradermacher/Qwen3.5-13B-GLM-4.7-Flash-DeepSeek-Polaris-Grande-Deep-Thinking-i1-GGUF | mradermacher | 2026-03-15T17:08:09Z | 1,327 | 2 | transformers | [
"transformers",
"gguf",
"unsloth",
"fine tune",
"all use cases",
"coder",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"romance",
"all genres",
... | null | 2026-03-15T16:29:50Z | ## 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_... | [
{
"start": 663,
"end": 734,
"text": "Qwen3.5-13B-GLM-4.7-Flash-DeepSeek-Polaris-Grande-Deep-Thinking-i1-GGUF",
"label": "benchmark name",
"score": 0.7091988921165466
},
{
"start": 808,
"end": 876,
"text": "Qwen3.5-13B-GLM-4.7-Flash-DeepSeek-Polaris-Grande-Deep-Thinking-GGUF",
... |
mradermacher/Ministral-3-14B-Base-2512-i1-GGUF | mradermacher | 2025-12-04T19:46:51Z | 125 | 2 | transformers | [
"transformers",
"gguf",
"mistral-common",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"base_model:mistralai/Ministral-3-14B-Base-2512",
"base_model:quantized:mistralai/Ministral-3-14B-Base-2512",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"... | null | 2025-12-02T18:47:34Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [
{
"start": 627,
"end": 660,
"text": "Ministral-3-14B-Base-2512-i1-GGUF",
"label": "benchmark name",
"score": 0.6966809034347534
},
{
"start": 734,
"end": 764,
"text": "Ministral-3-14B-Base-2512-GGUF",
"label": "benchmark name",
"score": 0.614447832107544
},
{
"sta... |
Alibaba-NLP/GVE-3B | Alibaba-NLP | 2025-11-03T08:30:18Z | 712 | 16 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"feature-extraction",
"pytorch",
"video",
"retrieval",
"embedding",
"multimodal",
"qwen2.5-vl",
"sentence-similarity",
"custom_code",
"en",
"dataset:Alibaba-NLP/UVRB",
"dataset:Vividbot/vast-2m-vi",
"dataset:TempoFunk/webvid-10M",
"dataset... | sentence-similarity | 2025-10-31T09:10:51Z | # 🎯 General Video Embedder (GVE)
> **One Embedder for All Video Retrieval Scenarios**
> Queries of text, image, video, or any combination modalities — GVE understands them all for representations, zero-shot, without in-domain training.
GVE is the first video embedding model that **generalizes across 9 abilities, i... | [
{
"start": 527,
"end": 562,
"text": "Universal Video Retrieval Benchmark",
"label": "benchmark name",
"score": 0.8262231945991516
},
{
"start": 564,
"end": 568,
"text": "UVRB",
"label": "benchmark name",
"score": 0.842627763748169
},
{
"start": 696,
"end": 700... |
microsoft/swin-base-patch4-window12-384-in22k | microsoft | 2022-05-16T18:01:06Z | 45,747 | 3 | transformers | [
"transformers",
"pytorch",
"tf",
"swin",
"image-classification",
"vision",
"dataset:imagenet-21k",
"arxiv:2103.14030",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"deploy:azure"
] | image-classification | 2022-03-02T23:29:05Z | # Swin Transformer (large-sized model)
Swin Transformer model pre-trained on ImageNet-21k (14 million images, 21,841 classes) at resolution 384x384. It was introduced in the paper [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030) by Liu et al. and first releas... | [] |
ibm-granite/granite-4.0-h-tiny-base | ibm-granite | 2025-11-03T19:43:45Z | 2,385 | 33 | transformers | [
"transformers",
"safetensors",
"granitemoehybrid",
"text-generation",
"language",
"granite-4.0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-16T19:55:02Z | [](https://mot.isitopen.ai/model/1167)
# Granite-4.0-H-Tiny-Base
**Model Summary:**
Granite-4.0-H-Tiny-Base is a decoder-only, long-context language model designed for a wide range of text-to-text generation tasks. It also ... | [] |
mradermacher/solidity-vuln-auditor-7b-GGUF | mradermacher | 2026-03-16T17:56:12Z | 503 | 1 | transformers | [
"transformers",
"gguf",
"base_model:adapter:zkaedi/solidity-vuln-auditor-7b",
"dpo",
"lora",
"sft",
"trl",
"unsloth",
"en",
"base_model:zkaedi/solidity-vuln-auditor-7b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-10T14:52:53Z | ## 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... | [] |
FlameF0X/ChessSLM-RL | FlameF0X | 2026-03-31T06:16:03Z | 442 | 2 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"chess",
"sefl-play",
"base_model:FlameF0X/ChessSLM",
"base_model:finetune:FlameF0X/ChessSLM",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-13T20:55:55Z | # ChessSLM-RL
**ChessSLM-RL** is the improve version of **ChessSLM** (a small language model designed to play chess using natural language move generation.) by using RL (Reinforcement LeanLearning) to make the model to hallucinated less and play a bit more conscious.
Despite having only **30M parameters**, it is capab... | [
{
"start": 1241,
"end": 1244,
"text": "Elo",
"label": "evaluation metric",
"score": 0.7882168889045715
},
{
"start": 1339,
"end": 1349,
"text": "Elo Rating",
"label": "evaluation metric",
"score": 0.8072764277458191
}
] |
Qwen/Qwen2-1.5B-Instruct | Qwen | 2024-06-06T14:36:57Z | 3,147,801 | 162 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-generation | 2024-06-03T09:08:12Z | # Qwen2-1.5B-Instruct
## Introduction
Qwen2 is the new series of Qwen large language models. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the instruction-tuned 1.5B Qwen2... | [
{
"start": 40,
"end": 45,
"text": "Qwen2",
"label": "benchmark name",
"score": 0.774744987487793
},
{
"start": 99,
"end": 104,
"text": "Qwen2",
"label": "benchmark name",
"score": 0.7652451395988464
},
{
"start": 315,
"end": 320,
"text": "Qwen2",
"labe... |
mradermacher/L3-70B-Euryale-v2.1-GGUF | mradermacher | 2024-12-05T05:05:51Z | 159 | 3 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Sao10K/L3-70B-Euryale-v2.1",
"base_model:quantized:Sao10K/L3-70B-Euryale-v2.1",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2024-12-04T10:57:14Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
static quants of https://huggingface.co/Sao10K/L3-70B-Euryale-v2.1
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.... | [] |
gordicaleksa/YugoGPT | gordicaleksa | 2024-02-22T15:29:25Z | 317 | 41 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-02-22T14:51:21Z | This repo contains YugoGPT - the best open-source base 7B LLM for BCS (Bosnian, Croatian, Serbian) languages developed by Aleksa Gordić.
You can access more powerful iterations of YugoGPT already through the recently announced [RunaAI's API platform](https://dev.runaai.com/)!
Serbian LLM eval results compared to Mist... | [] |
DeltaKX/translategemma-27b-it-Q4_K_M-GGUF | DeltaKX | 2026-01-19T02:00:38Z | 115 | 1 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"base_model:google/translategemma-27b-it",
"base_model:quantized:google/translategemma-27b-it",
"license:gemma",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-01-19T01:58:23Z | # DeltaKX/translategemma-27b-it-Q4_K_M-GGUF
This model was converted to GGUF format from [`google/translategemma-27b-it`](https://huggingface.co/google/translategemma-27b-it) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](h... | [] |
mlx-community/Voxtral-Mini-4B-Realtime-2602-fp16 | mlx-community | 2026-02-09T22:32:06Z | 217 | 2 | mlx | [
"mlx",
"safetensors",
"voxtral_realtime",
"mlx-audio",
"speech-to-text",
"streaming",
"realtime",
"automatic-speech-recognition",
"ar",
"de",
"en",
"es",
"fr",
"hi",
"it",
"nl",
"pt",
"zh",
"ja",
"ko",
"ru",
"base_model:mistralai/Voxtral-Mini-4B-Realtime-2602",
"base_mode... | automatic-speech-recognition | 2026-02-06T05:21:41Z | # Voxtral Mini 4B Realtime — MLX fp16
This is a **float16** [MLX](https://github.com/ml-explore/mlx) conversion of [mistralai/Voxtral-Mini-4B-Realtime-2602](https://huggingface.co/mistralai/Voxtral-Mini-4B-Realtime-2602), Mistral AI's streaming speech-to-text model.
Runs via [mlx-audio](https://github.com/Blaizzy/mlx... | [] |
mradermacher/Huihui-gemma-4-26B-A4B-it-abliterated-i1-GGUF | mradermacher | 2026-04-21T15:03:20Z | 9,461 | 3 | transformers | [
"transformers",
"gguf",
"abliterated",
"uncensored",
"en",
"base_model:huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated",
"base_model:quantized:huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-04-12T11:26:45Z | ## 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_... | [] |
allenai/MolmoWeb-4B | allenai | 2026-04-10T20:50:39Z | 2,768 | 32 | transformers | [
"transformers",
"safetensors",
"molmo2",
"image-text-to-text",
"multimodal",
"olmo",
"molmo",
"conversational",
"custom_code",
"en",
"dataset:allenai/MolmoWeb-SyntheticTraj",
"dataset:allenai/MolmoWeb-HumanTrajs",
"dataset:allenai/MolmoWeb-HumanSkills",
"dataset:allenai/MolmoWeb-SyntheticS... | image-text-to-text | 2026-03-20T04:12:11Z | <img src="molmoweb_logo.png" alt="Logo for the MolmoWeb Project" style="width: auto; height: 50px;">
# MolmoWeb-4B
<span style="color:red; font-weight: bold;">Important Update!</span>
We made a few small but important updates to this HF/transformers-compatible checkpoint to ensure exact outputs to our native model c... | [] |
MoritzLaurer/deberta-v3-large-zeroshot-v2.0 | MoritzLaurer | 2024-04-11T13:42:28Z | 296,374 | 125 | transformers | [
"transformers",
"onnx",
"safetensors",
"deberta-v2",
"text-classification",
"zero-shot-classification",
"en",
"arxiv:2312.17543",
"base_model:microsoft/deberta-v3-large",
"base_model:quantized:microsoft/deberta-v3-large",
"license:mit",
"endpoints_compatible",
"region:us"
] | zero-shot-classification | 2024-04-01T10:14:16Z | # Model description: deberta-v3-large-zeroshot-v2.0
## zeroshot-v2.0 series of models
Models in this series are designed for efficient zeroshot classification with the Hugging Face pipeline.
These models can do classification without training data and run on both GPUs and CPUs.
An overview of the latest zeroshot cl... | [] |
AesSedai/MiMo-V2.5-GGUF | AesSedai | 2026-05-04T07:34:43Z | 4,212 | 27 | null | [
"gguf",
"base_model:XiaomiMiMo/MiMo-V2.5",
"base_model:quantized:XiaomiMiMo/MiMo-V2.5",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-04-29T01:54:42Z | ## Notes
- 05/03/26: WIP vision support on this branch: https://github.com/AesSedai/llama.cpp/tree/mimo-v2.5-vision (if it's broken with F16 mmproj, pull the latest commit and recompile) and uploaded mmproj files
- 05/01/26: This branch includes CUDA flash attention, should speed up PP / TG: https://github.com/AesSedai... | [] |
amd/Llama-3.1-8B-Instruct-FP8-KV | amd | 2024-12-19T21:23:09Z | 33,108 | 7 | null | [
"safetensors",
"llama",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:quantized:meta-llama/Llama-3.1-8B-Instruct",
"license:other",
"fp8",
"region:us"
] | null | 2024-09-09T07:12:55Z | # Meta-Llama-3.1-8B-Instruct-FP8-KV
- ## Introduction
This model was created by applying [Quark](https://quark.docs.amd.com/latest/index.html) with calibration samples from Pile dataset.
- ## Quantization Stragegy
- ***Quantized Layers***: All linear layers excluding "lm_head"
- ***Weight***: FP8 symmetric per-te... | [
{
"start": 300,
"end": 324,
"text": "FP8 symmetric per-tensor",
"label": "evaluation metric",
"score": 0.9022597074508667
},
{
"start": 347,
"end": 371,
"text": "FP8 symmetric per-tensor",
"label": "evaluation metric",
"score": 0.8945606350898743
},
{
"start": 392... |
RedHatAI/MiniMax-M2.5 | RedHatAI | 2026-04-28T22:14:59Z | 298 | 1 | transformers | [
"transformers",
"safetensors",
"minimax_m2",
"text-generation",
"conversational",
"custom_code",
"en",
"license:other",
"endpoints_compatible",
"fp8",
"region:us"
] | text-generation | 2026-02-26T23:01:27Z | <h1 align: center; style="display: flex; align-items: center; gap: 10px; margin: 0;">
MiniMax-M2.5
<img src="https://www.redhat.com/rhdc/managed-files/Catalog-Validated_model_0.png" alt="Model Icon" width="40" style="margin: 0; padding: 0;" />
</h1>
<a href="https://www.redhat.com/en/products/ai/validated-models" t... | [] |
ai-sage/GigaChat3-702B-A36B-preview | ai-sage | 2025-11-24T13:16:09Z | 248 | 87 | transformers | [
"transformers",
"safetensors",
"deepseek_v3",
"text-generation",
"moe",
"conversational",
"ru",
"en",
"base_model:ai-sage/GigaChat3-702B-A36B-preview-bf16",
"base_model:quantized:ai-sage/GigaChat3-702B-A36B-preview-bf16",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
... | text-generation | 2025-11-19T17:59:03Z | # GigaChat 3 Ultra Preview
Представляем `GigaChat 3 Ultra Preview` — флагманскую **instruct-модель** семейства GigaChat.
Модель основана на архитектуре Mixture-of-Experts (MoE) с 702B общих и 36B активных параметров.
Архитектура включает **Multi-head Latent Attention (MLA)** и **Multi-Token Prediction (MTP)**, за сч... | [
{
"start": 2062,
"end": 2068,
"text": "Metric",
"label": "evaluation metric",
"score": 0.6424434781074524
}
] |
mradermacher/MetaphorStar-3B-GGUF | mradermacher | 2026-02-13T16:30:19Z | 102 | 1 | transformers | [
"transformers",
"gguf",
"vision-language-model",
"reinforcement-learning",
"grpo",
"metaphor-understanding",
"visual-reasoning",
"en",
"base_model:MING-ZCH/MetaphorStar-3B",
"base_model:quantized:MING-ZCH/MetaphorStar-3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"convers... | reinforcement-learning | 2026-02-13T16:03:48Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [
{
"start": 361,
"end": 376,
"text": "MetaphorStar-3B",
"label": "benchmark name",
"score": 0.7340645790100098
},
{
"start": 513,
"end": 533,
"text": "MetaphorStar-3B-GGUF",
"label": "benchmark name",
"score": 0.7540813684463501
},
{
"start": 1101,
"end": 1121,... |
csebuetnlp/banglat5 | csebuetnlp | 2022-08-21T13:59:20Z | 2,085 | 21 | transformers | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"bn",
"arxiv:2205.11081",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | 2022-05-23T07:51:38Z | # BanglaT5
This repository contains the pretrained checkpoint of the model **BanglaT5**. This is a sequence to sequence transformer model pretrained with the ["Span Corruption"]() objective. Finetuned models using this checkpoint achieve state-of-the-art results on many of the NLG tasks in bengali.
For finetuning on... | [
{
"start": 2,
"end": 10,
"text": "BanglaT5",
"label": "benchmark name",
"score": 0.7252082228660583
},
{
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"end": 86,
"text": "BanglaT5",
"label": "benchmark name",
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},
{
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"text": "banglat5",... |
burakaytan/roberta-base-turkish-uncased | burakaytan | 2022-09-07T05:44:18Z | 117 | 18 | transformers | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"tr",
"license:mit",
"endpoints_compatible",
"region:us"
] | fill-mask | 2022-04-20T06:08:13Z | 🇹🇷 RoBERTaTurk
## Model description
This is a Turkish RoBERTa base model pretrained on Turkish Wikipedia, Turkish OSCAR, and some news websites.
The final training corpus has a size of 38 GB and 329.720.508 sentences.
Thanks to Turkcell we could train the model on Intel(R) Xeon(R) Gold 6230R CPU @ 2.10GHz 256GB RA... | [] |
UnipatAI/UniScientist-30B-A3B | UnipatAI | 2026-03-04T12:56:48Z | 599 | 13 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"conversational",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-04T11:20:46Z | # Introduction
We present **UniScientist**, an agentic large language model featuring 30 billion total parameters, with only 3 billion activated per token. Developed by UniPat AI, the model is specifically designed for **universal scientific research** tasks spanning 50+ disciplines. UniScientist achieves state-of-the... | [
{
"start": 29,
"end": 41,
"text": "UniScientist",
"label": "benchmark name",
"score": 0.7593587636947632
},
{
"start": 286,
"end": 298,
"text": "UniScientist",
"label": "benchmark name",
"score": 0.6580422520637512
},
{
"start": 386,
"end": 410,
"text": "F... |
mradermacher/InfiAlign-Qwen-7B-DPO-i1-GGUF | mradermacher | 2025-12-09T03:24:55Z | 128 | 1 | transformers | [
"transformers",
"gguf",
"large-language-models",
"DPO",
"direct-preference-optimization",
"reasoning",
"long-CoT",
"en",
"base_model:InfiX-ai/InfiAlign-Qwen-7B-DPO",
"base_model:quantized:InfiX-ai/InfiAlign-Qwen-7B-DPO",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",... | null | 2025-08-12T22:28:14Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [
{
"start": 621,
"end": 650,
"text": "InfiAlign-Qwen-7B-DPO-i1-GGUF",
"label": "benchmark name",
"score": 0.6828206181526184
},
{
"start": 1211,
"end": 1240,
"text": "InfiAlign-Qwen-7B-DPO-i1-GGUF",
"label": "benchmark name",
"score": 0.6275706887245178
},
{
"start... |
mistralai/Ministral-8B-Instruct-2410 | mistralai | 2025-07-31T10:39:07Z | 189,127 | 576 | vllm | [
"vllm",
"safetensors",
"mistral",
"mistral-common",
"en",
"fr",
"de",
"es",
"it",
"pt",
"zh",
"ja",
"ru",
"ko",
"license:other",
"region:us"
] | null | 2024-10-15T09:20:23Z | # Model Card for Ministral-8B-Instruct-2410
We introduce two new state-of-the-art models for local intelligence, on-device computing, and at-the-edge use cases. We call them les Ministraux: Ministral 3B and Ministral 8B.
The Ministral-8B-Instruct-2410 Language Model is an instruct fine-tuned model significantly outp... | [] |
LCO-Embedding/LCO-Embedding-Omni-3B | LCO-Embedding | 2026-04-25T15:44:16Z | 2,323 | 9 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"qwen2_5_omni_thinker",
"image-text-to-text",
"transformers",
"feature-extraction",
"multimodal-embedding",
"arxiv:2510.11693",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2025-10-23T04:15:32Z | # LCO-Embedding: Scaling Language-Centric Omnimodal Representation Learning
We are thrilled to release LCO-Embedding - a language-centric omnimodal representation learning framework and the LCO-Embedding model families!
This model implements the framework presented in the paper [Scaling Language-Centric Omnimodal Rep... | [] |
wangkanai/wan22-fp16-encoders-gguf | wangkanai | 2025-10-28T05:18:33Z | 273 | 3 | diffusers | [
"diffusers",
"gguf",
"wan",
"text-to-video",
"image-generation",
"license:other",
"endpoints_compatible",
"region:us"
] | text-to-video | 2025-10-27T16:12:35Z | <!-- README Version: v1.1 -->
# WAN 2.2 FP16 Text Encoders (GGUF Format)
High-precision FP16 text encoders for the WAN 2.2 (World Animated Network) video generation model in optimized GGUF format. These encoders provide enhanced text understanding and conditioning for high-quality text-to-video and image-to-video gen... | [] |
CardinalOperations/ORLM-LLaMA-3-8B | CardinalOperations | 2025-04-03T03:23:18Z | 208 | 12 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:2405.17743",
"license:llama3",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-05-29T10:25:44Z | see our paper in https://arxiv.org/abs/2405.17743
github repo: https://github.com/Cardinal-Operations/ORLM
## Model Details
LLaMA-3-8B-ORLM is fully fine-tuned on the OR-Instruct data and built with Meta [LLaMA-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) model.
More training details can be seen at http... | [] |
deepseek-ai/deepseek-moe-16b-base | deepseek-ai | 2024-01-12T03:12:15Z | 27,560 | 142 | transformers | [
"transformers",
"safetensors",
"deepseek",
"text-generation",
"custom_code",
"arxiv:2401.06066",
"license:other",
"region:us"
] | text-generation | 2024-01-08T09:45:58Z | <p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://discor... | [] |
openbmb/AgentCPM-Report | openbmb | 2026-02-11T11:06:17Z | 283 | 247 | transformers | [
"transformers",
"safetensors",
"minicpm",
"feature-extraction",
"agent",
"text-generation-inference",
"text-generation",
"conversational",
"custom_code",
"arxiv:2602.06540",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-01-19T03:47:39Z | # AgentCPM-Report: Gemini-2.5-pro-DeepResearch Level Local DeepResearch
<p align="center">
<a href='https://huggingface.co/openbmb/AgentCPM-Report'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-AgentCPM--Report-yellow'>
<a href='https://huggingface.co/openbmb/AgentCPM-Report-GGUF'><img src='http... | [] |
feedseawave/WeDLM-8B-Instruct-GGUF | feedseawave | 2026-01-10T13:45:57Z | 230 | 4 | gguf | [
"gguf",
"llama-cpp",
"wedlm",
"tencent",
"qwen3",
"quantized",
"text-generation",
"en",
"zh",
"base_model:tencent/WeDLM-8B-Instruct",
"base_model:quantized:tencent/WeDLM-8B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-01-09T22:30:32Z | # WeDLM-8B-Instruct-GGUF
**First GGUF quantization of Tencent WeDLM-8B-Instruct!**
Quantized using llama.cpp b7688.
Original model: [tencent/WeDLM-8B-Instruct](https://huggingface.co/tencent/WeDLM-8B-Instruct)
## About
WeDLM is an 8B parameter instruction-tuned model by Tencent, supporting English and Ch... | [] |
Intel/Qwen3-Coder-30B-A3B-Instruct-gguf-q4km-AutoRound | Intel | 2025-08-08T08:54:46Z | 290 | 12 | null | [
"gguf",
"text-generation",
"dataset:codeparrot/github-code-clean",
"arxiv:2309.05516",
"base_model:Qwen/Qwen3-Coder-30B-A3B-Instruct",
"base_model:quantized:Qwen/Qwen3-Coder-30B-A3B-Instruct",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-08-04T08:15:17Z | ## Model Details
This model is a gguf q4km format of [Qwen/Qwen3-Coder-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct) generated by [intel/auto-round](https://github.com/intel/auto-round) algorithm. Embedding layer and lm-head layer are fallback to 8 bits and non expert layers are fallba... | [] |
ajibawa-2023/Python-Code-33B | ajibawa-2023 | 2024-03-04T12:12:38Z | 1,008 | 9 | transformers | [
"transformers",
"pytorch",
"llama",
"text-generation",
"code",
"en",
"dataset:ajibawa-2023/Python-Code-23k-ShareGPT",
"license:cc-by-nc-nd-4.0",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2023-11-13T05:14:01Z | **Python-Code-33B**
Large Language Models (LLMs) are good with code generations. Sometimes LLMs do make mistakes in code generation. How about if they can give detailed explanation along with the code.
This is what I have tried over here. The base Llama-2 model was used for training purpose. It is trained on around 23... | [] |
PhilipC/HumanOmniV2 | PhilipC | 2025-07-07T06:54:13Z | 1,082 | 19 | transformers | [
"transformers",
"safetensors",
"qwen2_5_omni_thinker",
"text-generation",
"video-text-to-text",
"arxiv:2506.21277",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | video-text-to-text | 2025-06-30T13:10:21Z | # HumanOmniV2: From Understanding to Omni-Modal Reasoning with Context
- Paper: [HumanOmniV2: From Understanding to Omni-Modal Reasoning with Context](https://huggingface.co/papers/2506.21277) ([Arxiv](https://arxiv.org/abs/2506.21277))
- Code: [GitHub Repository](https://github.com/PhilipC/HumanOmniV2)
- [IntentBench... | [] |
mradermacher/gpt-oss-20b-heretic-GGUF | mradermacher | 2025-11-16T17:55:14Z | 1,167 | 13 | transformers | [
"transformers",
"gguf",
"vllm",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:p-e-w/gpt-oss-20b-heretic",
"base_model:quantized:p-e-w/gpt-oss-20b-heretic",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-16T17:29:30Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: MXFP4_MOE 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: -->... | [] |
Kijai/LTXV2_comfy | Kijai | 2026-02-22T13:27:50Z | 86,186 | 437 | null | [
"gguf",
"comfyui",
"license:other",
"region:us"
] | null | 2026-01-07T16:47:57Z | # 22th February 2026: Model loading change
Starting from this commit https://github.com/Comfy-Org/ComfyUI/commit/f266b8d352607799afb4adf339cdfa854025185e
Embedding connector has been moved from text encoder to diffusion model, so to continue using single files you now have to update KJNodes and use my loaders:
![im... | [] |
Minachist/Qwen3.6-35B-A3B-INT8-AutoRound | Minachist | 2026-04-27T04:41:24Z | 1,971 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3_5_moe",
"image-text-to-text",
"compressed-tensors",
"qwen3_6",
"int8",
"autoround",
"conversational",
"base_model:Qwen/Qwen3.6-35B-A3B",
"base_model:quantized:Qwen/Qwen3.6-35B-A3B",
"license:apache-2.0",
"endpoints_compatible",
"8-bit",
"auto-round",... | image-text-to-text | 2026-04-18T21:07:07Z | # Qwen3.6-35B-A3B INT8 AutoRound
This is an unofficial INT8 quantized version of the Qwen3.6-35B-A3B. It was created using [AutoRound](https://github.com/intel/auto-round).
## Available versions
* There are three versions.
* Main branch (gs-1) uses about 3.2GB less VRAM than the gs32 branch while maintaining nearly ... | [
{
"start": 436,
"end": 447,
"text": "w8a16-gs128",
"label": "benchmark name",
"score": 0.6309112906455994
},
{
"start": 454,
"end": 464,
"text": "w8a16-gs32",
"label": "benchmark name",
"score": 0.6768486499786377
},
{
"start": 833,
"end": 834,
"text": "Δ"... |
bartowski/ServiceNow-AI_Apriel-1.5-15b-Thinker-GGUF | bartowski | 2025-10-01T21:20:58Z | 545 | 6 | null | [
"gguf",
"image-text-to-text",
"base_model:ServiceNow-AI/Apriel-1.5-15b-Thinker",
"base_model:quantized:ServiceNow-AI/Apriel-1.5-15b-Thinker",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2025-10-01T16:14:25Z | ## Llamacpp imatrix Quantizations of Apriel-1.5-15b-Thinker by ServiceNow-AI
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/b6647">b6647</a> for quantization.
Original model: https://huggingface.co/ServiceNow-AI/Apriel-1.5-15b-T... | [
{
"start": 304,
"end": 326,
"text": "Apriel-1.5-15b-Thinker",
"label": "benchmark name",
"score": 0.6260244250297546
}
] |
nota-ai/bk-sdm-tiny | nota-ai | 2023-11-17T02:06:05Z | 1,318 | 30 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"dataset:ChristophSchuhmann/improved_aesthetics_6.5plus",
"arxiv:2305.15798",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 2023-07-12T10:53:04Z | # BK-SDM Model Card
Block-removed Knowledge-distilled Stable Diffusion Model (BK-SDM) is an architecturally compressed SDM for efficient general-purpose text-to-image synthesis. This model is bulit with (i) removing several residual and attention blocks from the U-Net of [Stable Diffusion v1.4]( https://huggingface.co/... | [] |
mradermacher/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated-i1-GGUF | mradermacher | 2025-12-25T03:18:26Z | 23,484 | 92 | transformers | [
"transformers",
"gguf",
"abliterated",
"uncensored",
"en",
"base_model:huihui-ai/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated",
"base_model:quantized:huihui-ai/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversati... | null | 2025-08-03T10:14:21Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
lmstudio-community/functiongemma-270m-it-GGUF | lmstudio-community | 2025-12-18T18:27:52Z | 789 | 1 | null | [
"gguf",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-17T19:47:00Z | ## 💫 Community Model> functiongemma-270m-it by google
*👾 [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**: [google](https://huggingface.co/google)<br>
**O... | [] |
nvidia/GR00T-N1.6-fractal | nvidia | 2025-12-15T22:51:32Z | 329 | 1 | null | [
"safetensors",
"Gr00tN1d6",
"robotics",
"dataset:nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim",
"arxiv:2503.14734",
"base_model:nvidia/GR00T-N1.6-3B",
"base_model:finetune:nvidia/GR00T-N1.6-3B",
"region:us"
] | robotics | 2025-12-05T04:51:09Z | <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/bad... | [] |
TIGER-Lab/EditReward-Qwen2.5-VL-7B | TIGER-Lab | 2025-12-23T06:53:41Z | 489 | 3 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"edit",
"reward",
"en",
"dataset:TIGER-Lab/EditReward-Data",
"arxiv:2509.26346",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"text-generation-inference",
... | image-text-to-text | 2025-10-06T13:03:23Z | <p align="center" width="100%">
<img src="https://github.com/TIGER-AI-Lab/EditReward/raw/main/assets/logo.png" width="50%">
</p>
<div align="center">
# EditReward: A Human-Aligned Reward Model for Instruction-Guided Image Editing
[](https... | [] |
telepix/PIXIE-Spell-Reranker-Preview-0.6B | telepix | 2026-04-02T02:22:18Z | 114 | 5 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"qwen3",
"sentence-similarity",
"cross-encoder",
"reranker",
"feature-extraction",
"telepix",
"text-ranking",
"license:apache-2.0",
"region:us"
] | text-ranking | 2025-09-19T00:32:26Z | <p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/61d6f4a4d49065ee28a1ee7e/V8n2En7BlMNHoi1YXVv8Q.png" width="400"/>
<p>
# PIXIE-Spell-Reranker-Preview-0.6B
**PIXIE-Spell-Reranker-Preview-0.6B** is a decoder-based reranker trained on Korean and English information retrieval dataset,... | [
{
"start": 160,
"end": 193,
"text": "PIXIE-Spell-Reranker-Preview-0.6B",
"label": "benchmark name",
"score": 0.7846502065658569
},
{
"start": 196,
"end": 229,
"text": "PIXIE-Spell-Reranker-Preview-0.6B",
"label": "benchmark name",
"score": 0.7767783999443054
},
{
... |
tjake/Llama-3.2-1B-Instruct-JQ4 | tjake | 2024-10-19T20:08:05Z | 1,314 | 4 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"conversational",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"arxiv:2204.05149",
"license:llama3.2",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure"... | text-generation | 2024-10-19T20:07:45Z | # Quantized Version of meta-llama/Llama-3.2-1B-Instruct
This model is a quantized variant of the meta-llama/Llama-3.2-1B-Instruct model, optimized for use with Jlama, a Java-based inference engine. The quantization process reduces the model's size and improves inference speed, while maintaining high accuracy for effi... | [
{
"start": 1379,
"end": 1395,
"text": "Knowledge cutoff",
"label": "evaluation metric",
"score": 0.7501575350761414
}
] |
mradermacher/NVIDIA-Nemotron-3-Super-120B-A12B-BF16-heretic-GGUF | mradermacher | 2026-03-18T21:19:37Z | 3,520 | 2 | transformers | [
"transformers",
"gguf",
"nvidia",
"pytorch",
"nemotron-3",
"latent-moe",
"mtp",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"fr",
"es",
"it",
"de",
"ja",
"zh",
"dataset:nvidia/nemotron-post-training-v3",
"dataset:nvidia/nemotron-pre-training-datasets",
"base_m... | null | 2026-03-17T02:29:32Z | ## 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/Qwen_Qwen3.5-0.8B-GGUF | bartowski | 2026-03-10T02:51:42Z | 114,288 | 9 | null | [
"gguf",
"image-text-to-text",
"base_model:Qwen/Qwen3.5-0.8B",
"base_model:quantized:Qwen/Qwen3.5-0.8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2026-03-01T15:35:02Z | ## Llamacpp imatrix Quantizations of Qwen3.5-0.8B by Qwen
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/b8192">b8192</a> for quantization.
Original model: https://huggingface.co/Qwen/Qwen3.5-0.8B
All quants made using imatrix ... | [] |
zeon01/aiqarus-agent-4b | zeon01 | 2026-03-09T13:20:28Z | 105 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"tool-calling",
"agent",
"enterprise",
"qlora",
"fine-tuned",
"conversational",
"en",
"dataset:vericava/sft-tool-calling-structured-output-v1",
"dataset:interstellarninja/hermes_reasoning_tool_use",
"base_model:Qwen/Qwen3-4B-Instru... | text-generation | 2026-02-27T13:11:57Z | # aiqarus-agent-4b
A 4B parameter agent model fine-tuned from [Qwen3-4B-Instruct](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) for enterprise AI agent tasks: tool-calling, multi-step planning, risk escalation, confidence calibration, and multi-agent handoff.
Iteratively improved across two training rounds, wit... | [] |
mradermacher/Qwen3-VL-8B-Medical-Extraction-i1-GGUF | mradermacher | 2026-01-07T14:22:59Z | 1,881 | 1 | transformers | [
"transformers",
"gguf",
"en",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-11T08:57:29Z | ## 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_... | [] |
sapienzanlp/Minerva-7B-base-v1.0 | sapienzanlp | 2024-12-05T11:58:01Z | 1,403 | 15 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"pretrained",
"it",
"en",
"dataset:uonlp/CulturaX",
"dataset:HuggingFaceFW/fineweb",
"dataset:togethercomputer/RedPajama-Data-V2",
"dataset:bigcode/the-stack-v2",
"license:apache-2.0",
"text-generation-inference",
"endpoints_comp... | text-generation | 2024-05-26T19:34:19Z | <div style="text-align: center; display: flex; flex-direction: column; align-items: center;">
<img src="https://huggingface.co/sapienzanlp/Minerva-7B-instruct-v1.0/resolve/main/minerva-logo.png" style="max-width: 550px; height: auto;">
</div>
# Model Card for Minerva-7B-base-v1.0
Minerva is the first family of *... | [] |
LiquidAI/LFM2.5-350M | LiquidAI | 2026-04-01T19:39:31Z | 3,842 | 173 | transformers | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"liquid",
"lfm2.5",
"edge",
"conversational",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"pt",
"arxiv:2511.23404",
"base_model:LiquidAI/LFM2.5-350M-Base",
"base_model:finetune:LiquidAI/LFM2.5-350M-Base",
"license:... | text-generation | 2026-03-31T06:21:25Z | <div align="center">
<img
src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png"
alt="Liquid AI"
style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
/>
<div style="display: flex; ... | [] |
odats/rl_nmt_2026_04_11_13_41 | odats | 2026-04-13T15:16:59Z | 3,129 | 1 | transformers | [
"transformers",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"grpo",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:google/gemma-3-1b-it",
"base_model:finetune:google/gemma-3-1b-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-11T13:41:47Z | # Model Card for rl_nmt_2026_04_11_13_41
This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, b... | [] |
mradermacher/Qwen3-4B-Instruct-2507-uncensored-unslop-v2-GGUF | mradermacher | 2025-11-14T13:38:39Z | 196 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:electroglyph/Qwen3-4B-Instruct-2507-uncensored-unslop-v2",
"base_model:quantized:electroglyph/Qwen3-4B-Instruct-2507-uncensored-unslop-v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-13T19:39:10Z | ## 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/granite-4.0-h-small-MLX-6bit | lmstudio-community | 2025-09-29T20:34:36Z | 157 | 1 | transformers | [
"transformers",
"safetensors",
"granitemoehybrid",
"text-generation",
"language",
"granite-4.0",
"mlx",
"conversational",
"base_model:ibm-granite/granite-4.0-h-small",
"base_model:quantized:ibm-granite/granite-4.0-h-small",
"license:apache-2.0",
"endpoints_compatible",
"6-bit",
"region:us"... | text-generation | 2025-09-29T20:32:58Z | ## 💫 Community Model> granite-4.0-h-small by ibm-granite
_👾 [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**: [ibm-granite](https://huggingface.co/ibm-gra... | [] |
ibm-research/granite-guardian-3.2-3b-a800m-GGUF | ibm-research | 2025-03-28T14:02:38Z | 140 | 3 | transformers | [
"transformers",
"gguf",
"granite-3.2",
"guardian",
"text-generation",
"arxiv:2412.07724",
"base_model:ibm-granite/granite-guardian-3.2-3b-a800m",
"base_model:quantized:ibm-granite/granite-guardian-3.2-3b-a800m",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-03-21T18:09:01Z | > [!NOTE]
> This repository contains models that have been converted to the GGUF format with various quantizations from an IBM Granite base model.
>
> Please reference the base model's full model card here:
> https://huggingface.co/ibm-granite/granite-guardian-3.2-3b-a800m
# granite-guardian-3.2-3b-a800m-GGUF
## M... | [
{
"start": 548,
"end": 565,
"text": "IBM AI Risk Atlas",
"label": "benchmark name",
"score": 0.6315885186195374
}
] |
mradermacher/Qwen3.5-2B-GPT-5.1-HighIQ-INSTRUCT-i1-GGUF | mradermacher | 2026-03-04T10:11:41Z | 3,846 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"instruct",
"finetune",
"en",
"dataset:TeichAI/gpt-5.1-high-reasoning-1000x",
"base_model:DavidAU/Qwen3.5-2B-GPT-5.1-HighIQ-INSTRUCT",
"base_model:quantized:DavidAU/Qwen3.5-2B-GPT-5.1-HighIQ-INSTRUCT",
"license:apache-2.0",
"endpoints_compatible",
"region:us"... | null | 2026-03-04T09:52:08Z | ## 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": 634,
"end": 676,
"text": "Qwen3.5-2B-GPT-5.1-HighIQ-INSTRUCT-i1-GGUF",
"label": "benchmark name",
"score": 0.6544843316078186
}
] |
mispeech/midashenglm-7b-0804-fp32 | mispeech | 2026-03-17T04:28:42Z | 42,571 | 78 | null | [
"safetensors",
"midashenglm",
"multimodal",
"audio-language-model",
"audio",
"audio-text-to-text",
"custom_code",
"en",
"zh",
"th",
"id",
"vi",
"arxiv:2508.03983",
"base_model:Qwen/Qwen2.5-Omni-7B",
"base_model:finetune:Qwen/Qwen2.5-Omni-7B",
"license:apache-2.0",
"region:us"
] | audio-text-to-text | 2025-06-26T08:16:11Z | # MiDashengLM-7B-0804 - A general audio captioner
MiDashengLM is an efficient audio-language model that achieves holistic audio understanding through **caption-based** alignment.
It achieves state-of-the-art performance on multiple audio understanding benchmarks while maintaining high inference efficiency—delivering 3... | [] |
Synthyra/ESM2-650M | Synthyra | 2026-04-09T19:43:37Z | 285 | 1 | transformers | [
"transformers",
"safetensors",
"fast_esm",
"fill-mask",
"custom_code",
"arxiv:2412.05496",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-01-16T18:26:02Z | # NOTE
The GitHub with the implementation and requirements.txt can be found [here](https://github.com/Synthyra/FastPLMs.git)
# FastESM
FastESM is a Huggingface compatible plug in version of ESM2 rewritten with a newer PyTorch attention implementation.
Load any ESM2 models into a FastEsm model to dramatically sp... | [] |
nu-dialogue/j-moshi | nu-dialogue | 2025-06-04T01:56:07Z | 163 | 15 | moshi | [
"moshi",
"safetensors",
"ja",
"dataset:sarulab-speech/J-CHAT",
"arxiv:2506.02979",
"arxiv:2410.00037",
"arxiv:2407.15828",
"arxiv:2109.05217",
"base_model:kyutai/moshiko-pytorch-bf16",
"base_model:finetune:kyutai/moshiko-pytorch-bf16",
"license:cc-by-nc-4.0",
"region:us"
] | null | 2025-01-21T15:23:45Z | [](README-en.md) [](LICENSE)
[📑 **Paper**](http://arxiv.org/abs/2506.02979)
|
[🤗 **Model**](https://huggingface.co/nu-dialogue/j-moshi-ext)
|
[🖥️ **Demo**](ht... | [] |
unsloth/gemma-4-31B-it-GGUF | unsloth | 2026-05-04T09:17:05Z | 1,770,705 | 392 | null | [
"gguf",
"gemma4",
"unsloth",
"gemma",
"google",
"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 | 2026-04-01T14:40:18Z | # Read our How to [Run Gemma 4 Guide!](https://docs.unsloth.ai/models/gemma-4)
<div>
<p style="margin: 0 0 0px 0; margin-top: 0px;">
<em>See <a href="https://unsloth.ai/docs/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0 GGUFs</a> for our quantization benchmarks.</em>
</p>
<div style="display: flex; ga... | [
{
"start": 23,
"end": 30,
"text": "Gemma 4",
"label": "benchmark name",
"score": 0.6653432846069336
},
{
"start": 70,
"end": 77,
"text": "gemma-4",
"label": "benchmark name",
"score": 0.6785122752189636
},
{
"start": 740,
"end": 747,
"text": "gemma-4",
... |
mradermacher/Nemotron-Nano-9B-v2-heretic-i1-GGUF | mradermacher | 2026-03-20T17:45:52Z | 2,165 | 1 | transformers | [
"transformers",
"gguf",
"nvidia",
"pytorch",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"es",
"fr",
"de",
"it",
"ja",
"dataset:nvidia/Nemotron-Post-Training-Dataset-v1",
"dataset:nvidia/Nemotron-Post-Training-Dataset-v2",
"dataset:nvidia/Nemotron-Pretraining-Dataset-... | null | 2026-03-20T15:26:34Z | ## 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": 626,
"end": 661,
"text": "Nemotron-Nano-9B-v2-heretic-i1-GGUF",
"label": "benchmark name",
"score": 0.722961962223053
},
{
"start": 735,
"end": 767,
"text": "Nemotron-Nano-9B-v2-heretic-GGUF",
"label": "benchmark name",
"score": 0.6291353702545166
},
{
... |
Qwen/Qwen2-VL-2B | Qwen | 2024-12-06T04:50:16Z | 3,415 | 61 | transformers | [
"transformers",
"safetensors",
"qwen2_vl",
"image-text-to-text",
"multimodal",
"conversational",
"en",
"arxiv:2409.12191",
"arxiv:2308.12966",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | image-text-to-text | 2024-09-05T07:14:45Z | # Qwen2-VL-2B
## Introduction
We're excited to unveil **Qwen2-VL**, the latest iteration of our Qwen-VL model, representing nearly a year of innovation.
> [!Important]
> This is the base pretrained model of Qwen2-VL-2B without instruction tuning.
### What’s New in Qwen2-VL?
#### Key Enhancements:
* **SoTA unders... | [
{
"start": 464,
"end": 473,
"text": "MathVista",
"label": "benchmark name",
"score": 0.8147047758102417
},
{
"start": 475,
"end": 481,
"text": "DocVQA",
"label": "benchmark name",
"score": 0.7990824580192566
},
{
"start": 483,
"end": 494,
"text": "RealWorl... |
mradermacher/EVisRAG-7B-i1-GGUF | mradermacher | 2025-12-06T07:15:49Z | 178 | 1 | transformers | [
"transformers",
"gguf",
"en",
"dataset:openbmb/EVisRAG-Train",
"base_model:Boggy666/EVisRAG-7B",
"base_model:quantized:Boggy666/EVisRAG-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-10-18T23:47:19Z | ## 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": 611,
"end": 629,
"text": "EVisRAG-7B-i1-GGUF",
"label": "benchmark name",
"score": 0.7188528180122375
},
{
"start": 703,
"end": 718,
"text": "EVisRAG-7B-GGUF",
"label": "benchmark name",
"score": 0.6392167806625366
},
{
"start": 840,
"end": 855,
... |
onnx-community/moonshine-tiny-ja-ONNX | onnx-community | 2026-02-04T20:19:00Z | 220 | 1 | transformers.js | [
"transformers.js",
"onnx",
"moonshine",
"automatic-speech-recognition",
"ja",
"arxiv:2509.02523",
"arxiv:1810.03993",
"base_model:UsefulSensors/moonshine-tiny-ja",
"base_model:quantized:UsefulSensors/moonshine-tiny-ja",
"license:other",
"region:us"
] | automatic-speech-recognition | 2026-02-04T20:18:56Z | # moonshine-tiny-ja (ONNX)
This is an ONNX version of [UsefulSensors/moonshine-tiny-ja](https://huggingface.co/UsefulSensors/moonshine-tiny-ja). It was automatically converted and uploaded using [this Hugging Face Space](https://huggingface.co/spaces/onnx-community/convert-to-onnx).
## Usage with Transformers.js
... | [] |
kandinskylab/Kandinsky-5.0-I2I-Lite-sft-Diffusers | kandinskylab | 2025-11-24T15:43:39Z | 138 | 6 | diffusers | [
"diffusers",
"safetensors",
"image-to-image",
"arxiv:2511.14993",
"base_model:kandinskylab/Kandinsky-5.0-I2I-Lite-pretrain-Diffusers",
"base_model:finetune:kandinskylab/Kandinsky-5.0-I2I-Lite-pretrain-Diffusers",
"license:mit",
"diffusers:Kandinsky5T2IPipeline",
"region:us"
] | image-to-image | 2025-11-19T09:50:31Z | <div align="center">
<picture>
<img src="assets/KANDINSKY_LOGO_1_BLACK.png">
</picture>
</div>
<div align="center">
<a href="https://habr.com/ru/companies/sberbank/articles/951800/">Habr</a> |
<a href="https://ai-forever.github.io/Kandinsky-5/">Project Page</a> |
<a href="https://arxiv.org/abs/2511.14993... | [] |
Mungert/VibeThinker-1.5B-GGUF | Mungert | 2025-11-11T13:47:11Z | 336 | 4 | transformers | [
"transformers",
"gguf",
"math",
"code",
"gpqa",
"text-generation",
"en",
"arxiv:2511.06221",
"base_model:Qwen/Qwen2.5-Math-1.5B",
"base_model:quantized:Qwen/Qwen2.5-Math-1.5B",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-11-11T13:10:38Z | # <span style="color: #7FFF7F;">VibeThinker-1.5B GGUF Models</span>
## <span style="color: #7F7FFF;">Model Generation Details</span>
This model was generated using [llama.cpp](https://github.com/ggerganov/llama.cpp) at commit [`1d45b4228`](https://github.com/ggerganov/llama.cpp/commit/1d45b4228f11c193d6864724ae67573... | [
{
"start": 1265,
"end": 1271,
"text": "AIME24",
"label": "benchmark name",
"score": 0.8505876660346985
},
{
"start": 1273,
"end": 1279,
"text": "AIME25",
"label": "benchmark name",
"score": 0.8399654626846313
},
{
"start": 1285,
"end": 1291,
"text": "HMMT2... |
cirimus/modernbert-base-go-emotions | cirimus | 2026-03-17T13:01:50Z | 924 | 11 | transformers | [
"transformers",
"safetensors",
"modernbert",
"text-classification",
"pytorch",
"ModernBERT",
"emotions",
"multi-class-classification",
"multi-label-classification",
"en",
"dataset:go_emotions",
"base_model:answerdotai/ModernBERT-base",
"base_model:finetune:answerdotai/ModernBERT-base",
"li... | text-classification | 2025-01-14T16:59:51Z | 
# ModernBERT Go Emotions 2026-03
> Note: This version significantly improves the [baseline 2025 model](https://huggingface.co/cirimus/modernbert-base-go-emotions-2025-01).
### Overview
This model was fine-tuned fro... | [] |
jacehoi/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-GGUF | jacehoi | 2026-03-21T17:39:08Z | 635 | 1 | null | [
"gguf",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"Dense",
"text-generation",
"en",
"zh",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtered",
"dataset:Jackrong/Qwen3.5-reasoning-700x",
"base_model:Qwen/Qwen3.5-27B",
"base_model:quantized:Qwen/Qwen3.5-27B"... | text-generation | 2026-03-21T17:39:07Z | # 🌟 Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled
> 📢 **Release Note**
> **Build Environment Upgrades:**
> - **Fine-tuning Framework**: **Unsloth 2026.3.3**
> - **Core Dependencies**: **Transformers 5.2.0**
> - This model fixes the crash in the official model caused by the Jinja template not supporting the **"dev... | [] |
mradermacher/LFM2.5-VL-1.6B-absolute-heresy-MPOA-GGUF | mradermacher | 2026-02-11T07:09:33Z | 414 | 3 | transformers | [
"transformers",
"gguf",
"liquid",
"lfm2",
"lfm2-vl",
"edge",
"lfm2.5-vl",
"lfm2.5",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"ja",
"ko",
"fr",
"es",
"de",
"ar",
"zh",
"base_model:MuXodious/LFM2.5-VL-1.6B-absolute-heresy-MPOA",
"base_model:quantized:MuXodi... | null | 2026-02-11T07:07:36Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [
{
"start": 534,
"end": 574,
"text": "LFM2.5-VL-1.6B-absolute-heresy-MPOA-GGUF",
"label": "benchmark name",
"score": 0.6121652126312256
}
] |
leejet/Z-Image-Turbo-GGUF | leejet | 2025-12-02T12:31:06Z | 21,188 | 35 | null | [
"gguf",
"text-to-image",
"image-generation",
"stable-diffusion.cpp",
"z-image-turbo",
"z-image",
"en",
"zh",
"base_model:Tongyi-MAI/Z-Image-Turbo",
"base_model:quantized:Tongyi-MAI/Z-Image-Turbo",
"license:apache-2.0",
"region:us"
] | text-to-image | 2025-11-30T15:34:37Z | # Z-Image-Turbo GGUF quantized files
The license of the quantized files follows the license of the original model:
- Z-Image-Turbo: apache-2.0
These files are converted using https://github.com/leejet/stable-diffusion.cpp
You can use these weights with stable-diffusion.cpp to generate images.
## How to Use Z‐Image... | [] |
alibaba-pai/Wan2.2-Fun-A14B-Control | alibaba-pai | 2025-12-11T02:27:54Z | 1,913 | 79 | videox_fun | [
"videox_fun",
"diffusers",
"safetensors",
"video",
"video-generation",
"wan2.2",
"image-to-video",
"en",
"zh",
"base_model:Wan-AI/Wan2.2-I2V-A14B",
"base_model:finetune:Wan-AI/Wan2.2-I2V-A14B",
"license:apache-2.0",
"region:us"
] | image-to-video | 2025-08-05T02:40:12Z | # Wan-Fun
😊 Welcome!
[](https://huggingface.co/spaces/alibaba-pai/Wan2.1-Fun-1.3B-InP)
[](https://github.com/aigc-apps/VideoX-Fun)
[English](./README_en.md) |... | [] |
lmstudio-community/Qwen3-VL-4B-Instruct-GGUF | lmstudio-community | 2025-10-30T20:23:36Z | 54,729 | 5 | null | [
"gguf",
"base_model:Qwen/Qwen3-VL-4B-Instruct",
"base_model:quantized:Qwen/Qwen3-VL-4B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-30T20:21:34Z | ## 💫 Community Model> Qwen3-VL-4B-Instruct by Qwen
*👾 [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**: [Qwen](https://huggingface.co/Qwen)<br>
**Original... | [] |
prithivMLmods/Qwen3-VL-8B-Thinking-abliterated-v1 | prithivMLmods | 2025-11-12T21:50:29Z | 112 | 6 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"text-generation-inference",
"abliterated",
"v1.0",
"conversational",
"en",
"base_model:Qwen/Qwen3-VL-8B-Thinking",
"base_model:finetune:Qwen/Qwen3-VL-8B-Thinking",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-10-16T09:21:19Z | 
# **Qwen3-VL-8B-Thinking-abliterated**
> **Qwen3-VL-8B-Thinking-abliterated** is an abliterated (v1.0) variant of Qwen3-VL-8B-Thinking, designed for Abliterated Reasoning and Captioning.
> This model produce... | [] |
Jackrong/Gemopus-4-26B-A4B-it | Jackrong | 2026-04-10T23:31:46Z | 1,401 | 3 | null | [
"safetensors",
"gemma4",
"gemma",
"instruction-tuned",
"reasoning",
"alignment",
"text-generation",
"conversational",
"en",
"zh",
"ko",
"ja",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-09T07:51:32Z | # 🌟 Gemopus-4-26B-A4B-it
> [!NOTE]
> **Gemopus** is an attempt at fine-tuning Gemma 4 with a core philosophy of "stability first".
>
> While preserving the original reasoning order of **Gemma 4** as much as possible, we conducted targeted refinements for answer quality, structure, clarity, and consistency.
>
> **🍎... | [] |
OuteAI/OuteTTS-0.3-1B-GGUF | OuteAI | 2025-01-17T15:31:06Z | 820 | 31 | null | [
"gguf",
"text-to-speech",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-to-speech | 2025-01-13T20:04:39Z | <style>
table {
border-collapse: collapse;
width: 100%;
margin-bottom: 20px;
}
th, td {
border: 1px solid #ddd;
padding: 8px;
text-align: center;
}
.best {
font-weight: bold;
text-decoration: underline;
}
.box {
text-align: center;
margin: 20px auto;
padding: 30px;
box-shadow: 0p... | [] |
FrontiersMind/Nandi-Mini-150M-Tool-Calling | FrontiersMind | 2026-04-22T14:02:04Z | 2,457 | 35 | transformers | [
"transformers",
"safetensors",
"nandi",
"text-generation",
"conversational",
"custom_code",
"en",
"base_model:FrontiersMind/Nandi-Mini-150M",
"base_model:finetune:FrontiersMind/Nandi-Mini-150M",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-16T18:27:58Z | # Nandi-Mini-150M-Tool-Calling
## Introduction
Nandi-Mini-150M-Tool-Calling is a lightweight, single-turn specialized model designed to accurately interpret user queries and generate precise tool calls in one step, enabling efficient and reliable function execution
## 📝 Upcoming Releases & Roadmap
We’re just getti... | [
{
"start": 2,
"end": 30,
"text": "Nandi-Mini-150M-Tool-Calling",
"label": "benchmark name",
"score": 0.7222276926040649
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{
"start": 49,
"end": 77,
"text": "Nandi-Mini-150M-Tool-Calling",
"label": "benchmark name",
"score": 0.6423789858818054
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{
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... |
openpangu/openPangu-Ultra-MoE-718B-model | openpangu | 2026-04-15T12:31:02Z | 558 | 1 | null | [
"safetensors",
"pangu_ultra_moe",
"custom_code",
"region:us"
] | null | 2026-04-08T07:31:54Z | # 开源盘古 Ultra-MoE-718B
中文 | [English](README_EN.md)
## 1. 简介
openPangu-Ultra-MoE-718B 是基于昇腾NPU从零训练的大规模混合专家语言模型，总参数量为718B，激活参数量为39B。openPangu-Ultra-MoE-718B 训练了约19T tokens，具备快慢思考融合能力。
## 2. 模型架构
openPangu-Ultra-MoE-718B 的模型架构采用了业界主流的Multi-head Latent Attention (MLA)、Multi-Token Prediction (MTP)、大稀疏比等架构，以及一些特有的设计：
- De... | [
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"label": "benchmark name",
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"start": 682,
"end": 689,
"text": "CLUEWSC",
"label": "benchmark name",
"score": 0.6052551865577698
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large-traversaal/Alif-1.0-8B-Instruct | large-traversaal | 2025-10-13T04:48:28Z | 1,551 | 37 | transformers | [
"transformers",
"safetensors",
"gguf",
"llama",
"text-generation-inference",
"unsloth",
"trl",
"en",
"ur",
"arxiv:2510.09051",
"base_model:unsloth/Meta-Llama-3.1-8B",
"base_model:quantized:unsloth/Meta-Llama-3.1-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-01-28T14:02:23Z | # Model Card for Alif 1.0 8B Instruct
**Alif 1.0 8B Instruct** is an open-source model with highly advanced multilingual reasoning capabilities. It utilizes human refined multilingual synthetic data paired with reasoning to enhance cultural nuance and reasoning capabilities in english and urdu languages.
- **Develope... | [] |
allenai/Olmo-3.1-7B-RL-Zero-Code | allenai | 2026-01-05T16:25:15Z | 806 | 17 | transformers | [
"transformers",
"safetensors",
"olmo3",
"text-generation",
"conversational",
"en",
"dataset:allenai/Dolci-RL-Zero-Code-7B",
"arxiv:2512.13961",
"base_model:allenai/Olmo-3-1025-7B",
"base_model:finetune:allenai/Olmo-3-1025-7B",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"... | text-generation | 2025-12-10T23:48:17Z | ## Model Details
<img alt="Logo for Olmo 3 7B Zero model" src="olmo-rl-zero.png" width="268px" style="margin-left:'auto' margin-right:'auto' display:'block'">
# Model Card for Olmo 3.1 7B RL-Zero Code
We introduce Olmo 3, a new family of 7B and 32B models both Instruct and Think variants. Long chain-of-thought think... | [] |
iitolstykh/GigaCheck-Classifier-Multi | iitolstykh | 2026-04-21T15:16:12Z | 2,299 | 4 | gigacheck | [
"gigacheck",
"safetensors",
"mistral",
"text-classification",
"ai-detection",
"multilingual",
"custom_code",
"en",
"ru",
"dataset:iitolstykh/LLMTrace_classification",
"arxiv:2509.21269",
"arxiv:2410.23728",
"base_model:mistralai/Mistral-7B-v0.3",
"base_model:finetune:mistralai/Mistral-7B-v... | text-classification | 2025-09-25T08:24:45Z | # GigaCheck-Classifier-Multi
<p style="text-align: center;">
<div align="center">
<img src="https://raw.githubusercontent.com/sweetdream779/LLMTrace-info/refs/heads/main/images/logo/GigaCheck-classifier-multi.PNG" width="40%"/>
</div>
<p align="center">
<a href="https://sweetdream779.github.io/LLMTrace-info"... | [] |
p-e-w/gpt-oss-20b-heretic-v3 | p-e-w | 2026-02-14T07:26:48Z | 291 | 12 | transformers | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"vllm",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"arxiv:2508.10925",
"license:apache-2.0",
"endpoints_compatible",
"8-bit",
"mxfp4",
"region:us"
] | text-generation | 2026-02-14T07:25:15Z | # This is a decensored version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b), made using [Heretic](https://github.com/p-e-w/heretic) v1.1.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | per layer |
| **attn.o_proj.max_weight** | 1.47 |
| **attn.o_p... | [
{
"start": 360,
"end": 382,
"text": "attn.o_proj.min_weight",
"label": "evaluation metric",
"score": 0.6135091185569763
},
{
"start": 398,
"end": 429,
"text": "attn.o_proj.min_weight_distance",
"label": "evaluation metric",
"score": 0.6061724424362183
}
] |
mudler/Qwen3.5-397B-A17B-APEX-GGUF | mudler | 2026-04-27T14:00:26Z | 2,687 | 3 | null | [
"gguf",
"quantized",
"apex",
"moe",
"mixture-of-experts",
"qwen3.5",
"vlm",
"vision",
"base_model:Qwen/Qwen3.5-397B-A17B",
"base_model:quantized:Qwen/Qwen3.5-397B-A17B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-06T04:01:36Z | <!-- 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,
"end": 592,
"text": "APEX",
"label": "benchmark name",
"score": 0.6842774748802185
}
] |
trohrbaugh/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16-heretic | trohrbaugh | 2026-04-14T18:37:14Z | 2,973 | 1 | transformers | [
"transformers",
"safetensors",
"nemotron_h",
"text-generation",
"nvidia",
"pytorch",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"conversational",
"custom_code",
"en",
"es",
"fr",
"de",
"ja",
"it",
"dataset:nvidia/Nemotron-Pretraining-Code-v1",
"dataset:nvidi... | text-generation | 2026-03-18T01:33:30Z | # This is a decensored version of [nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0 with the [Arbitrary-Rank Ablation (ARA)](https://github.com/p-e-w/heretic/pull/211) method
## Abliteration par... | [] |
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