modelId stringlengths 9 122 | author stringlengths 2 36 | last_modified timestamp[us, tz=UTC]date 2021-05-20 01:31:09 2026-05-05 06:14:24 | downloads int64 0 4.03M | likes int64 0 4.32k | library_name stringclasses 189
values | tags listlengths 1 237 | pipeline_tag stringclasses 53
values | createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2026-05-05 05:54:22 | card stringlengths 500 661k | entities listlengths 0 12 |
|---|---|---|---|---|---|---|---|---|---|---|
inferencerlabs/Qwen3.5-0.8B-MLX-9bit | inferencerlabs | 2026-03-04T09:52:03Z | 282 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"quantized",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen3.5-0.8B",
"base_model:quantized:Qwen/Qwen3.5-0.8B",
"8-bit",
"region:us"
] | text-generation | 2026-03-04T09:44:56Z | **See Qwen3.5-0.8B MLX in action - [demonstration video - coming soon](https://youtu.be/tzF8jv3VGAg)**
#### Tested on a M3 Ultra 512GB RAM using [Inferencer app](https://inferencer.com)
- Single inference ~231.1 tokens/s @ 1000 tokens
- Batched inference ~ total tokens/s across five inferences
- Memory usage: ~0.84 Gi... | [] |
rbelanec/train_boolq_456_1765386945 | rbelanec | 2025-12-10T19:50:40Z | 1 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"ia3",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | null | 2025-12-10T17:16:17Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# train_boolq_456_1765386945
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/met... | [] |
AmanPriyanshu/gpt-oss-16.1b-specialized-health_or_medicine-pruned-moe-only-24-experts | AmanPriyanshu | 2025-08-13T06:21:17Z | 8 | 1 | null | [
"safetensors",
"gpt_oss",
"mixture-of-experts",
"moe",
"expert-pruning",
"gpt-oss",
"openai",
"reasoning",
"health-or-medicine",
"specialized",
"efficient",
"transformer",
"causal-lm",
"text-generation",
"pytorch",
"pruned-model",
"domain-specific",
"conversational",
"en",
"dat... | text-generation | 2025-08-13T06:20:25Z | # Health Or Medicine GPT-OSS Model (24 Experts)
**Project**: https://amanpriyanshu.github.io/GPT-OSS-MoE-ExpertFingerprinting/
<div align="center">
### 👥 Follow the Authors
**Aman Priyanshu**
[](https://www.l... | [] |
Whitewinter/model-merged | Whitewinter | 2026-03-05T13:42:52Z | 18 | 0 | null | [
"safetensors",
"qwen3",
"fine-tuned",
"merged",
"lora",
"qwen",
"ko",
"en",
"dataset:tatsu-lab/alpaca",
"base_model:Qwen/Qwen3-0.6B",
"base_model:adapter:Qwen/Qwen3-0.6B",
"license:apache-2.0",
"4-bit",
"bitsandbytes",
"region:us"
] | null | 2026-03-05T13:42:31Z | # Fine-tuned Merged Model
이 모델은 Qwen/Qwen3-0.6B을 기반으로 LoRA(Low-Rank Adaptation) 기법을 사용해 파인튜닝한 후, 기본 모델과 병합된 완전한 모델입니다.
## 모델 정보
- **베이스 모델**: Qwen/Qwen3-0.6B
- **파인튜닝 방법**: LoRA (Low-Rank Adaptation)
- **데이터셋**: tatsu-lab/alpaca
- **모델 타입**: 완전 병합된 모델 (Full Merged Model)
## 사용 방법
```python
from transformers import ... | [] |
alexandertam/babylm-base9m-roberta | alexandertam | 2025-08-21T12:25:57Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"fill-mask",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-08-21T12:25:34Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# babylm-base9m-roberta
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the fo... | [] |
spicyneuron/Qwen3.5-397B-A17B-MLX-3.5-bit | spicyneuron | 2026-03-22T23:42:31Z | 226 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3.5-397B-A17B",
"base_model:quantized:Qwen/Qwen3.5-397B-A17B",
"license:apache-2.0",
"3-bit",
"region:us"
] | text-generation | 2026-03-22T12:20:54Z | [Qwen3.5-397B-A17B](https://huggingface.co/Qwen/Qwen3.5-397B-A17B) optimized for MLX!
- Mixed-precision quantization balances throughput, accuracy, and memory.
- Better quality than a 4-bit baseline but requires 20% less memory.
- Fixed chat template allows more reliable prompt caching.
- This version does NOT support... | [] |
Zhaoming213/BackTo2012 | Zhaoming213 | 2026-03-16T16:52:45Z | 323 | 0 | null | [
"safetensors",
"llama",
"text-generation-inference",
"text-generation",
"conversational",
"zh",
"dataset:Zhaoming213/THUCNews2012",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-07T16:14:37Z | # BackTo2012
过去的时光总是那么的让人怀念，可是时间不能倒流（至少现在的技术不允许），那么，还想体验过去的时光怎么办？搭建一个拟物化的网站？但看起还是少点什么，没错，那是因为它是静态的，只有动态的内容才能让人产生心动！
尝试过使用大模型来怀旧？但是你会发现总是差那么一点，没错，那是因为大模型的知识比较新，而不是完全用2012年的视角来看，但是如果要是只用2012年的数据训练模型，效果会好很多！
这是一个仅用2012年的数据从头预训练的一个小模型，模型的知识截止日期是2012年，这意味着模型可以模仿早期互联网风格的内容用来怀旧！
## 简介
这是基于Github Minimind项目训练的模型！
地址是：ht... | [] |
Svetozar1993/MultilingualSTT | Svetozar1993 | 2026-01-13T15:18:46Z | 8 | 1 | transformers | [
"transformers",
"pytorch",
"jax",
"safetensors",
"whisper",
"automatic-speech-recognition",
"speech-recognition",
"multilingual",
"en",
"zh",
"de",
"es",
"ru",
"ko",
"fr",
"ja",
"pt",
"tr",
"pl",
"ca",
"nl",
"ar",
"sv",
"it",
"id",
"hi",
"fi",
"vi",
"he",
"u... | automatic-speech-recognition | 2026-01-13T11:00:51Z | # MultilingualSTT
OpenAI's Whisper Large V3 model for multilingual speech-to-text transcription.
## Model Description
Whisper Large V3 is a state-of-the-art automatic speech recognition (ASR) model that supports 99+ languages. It provides highly accurate transcription across a wide range of languages and acoustic co... | [] |
ShreyashDhoot/v3 | ShreyashDhoot | 2026-05-04T13:23:54Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"inpainting",
"lora",
"kto",
"image-to-image",
"base_model:runwayml/stable-diffusion-inpainting",
"base_model:adapter:runwayml/stable-diffusion-inpainting",
"license:creativeml-openrail-m",
"region:us"
] | image-to-image | 2026-04-28T06:51:58Z | # ShreyashDhoot/v3
**Last updated:** 2026-05-04 13:22
## Model Description
KTO fine-tuned Stable Diffusion inpainter with LoRA for safety alignment.
Base model: [`runwayml/stable-diffusion-inpainting`](https://huggingface.co/runwayml/stable-diffusion-inpainting)
## Checkpoints
- `checkpoint--1000`
- `checkpoint--1... | [] |
RukDias/m2m100-1.2B-singlish-lora | RukDias | 2026-01-17T15:47:12Z | 1 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:facebook/m2m100_1.2B",
"lora",
"transformers",
"base_model:facebook/m2m100_1.2B",
"license:mit",
"region:us"
] | null | 2026-01-17T15:02:23Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# m2m100-1.2B-singlish-lora
This model is a fine-tuned version of [facebook/m2m100_1.2B](https://huggingface.co/facebook/m2m100_1.2... | [] |
mradermacher/ADG-CoT-LLaMa3-8B-i1-GGUF | mradermacher | 2026-04-18T05:00:58Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"ADG",
"SFT",
"zh",
"en",
"base_model:WisdomShell/ADG-CoT-LLaMa3-8B",
"base_model:quantized:WisdomShell/ADG-CoT-LLaMa3-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2026-04-18T00:26:33Z | ## 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_... | [] |
lewei123/Qwen3-VL-8B-Base-woDS-stage0-Seed42 | lewei123 | 2026-02-03T12:03:20Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"conversational",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-02-03T12:02:21Z | <a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
# Qwen3-VL-8B-Instruct
Meet Qwen3-VL — the most powerful vision-language model in... | [] |
ggml-org/SmolLM3-3B-GGUF | ggml-org | 2025-07-08T23:36:47Z | 5,416 | 54 | null | [
"gguf",
"en",
"fr",
"es",
"it",
"pt",
"zh",
"ar",
"ru",
"base_model:HuggingFaceTB/SmolLM3-3B",
"base_model:quantized:HuggingFaceTB/SmolLM3-3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-07-08T12:36:39Z | # SmolLM3-GGUF
Original model: https://huggingface.co/HuggingFaceTB/SmolLM3-3B
> [!IMPORTANT]
> To enable thinking, you need to specify `--jinja`
Example usage with llama.cpp:
```
llama-cli -hf ggml-org/SmolLM3-3B-GGUF --jinja
```
![image/png](https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce... | [] |
fdk6566/wan2.2_14b_i2v_480p_lightning_nsfw_diffusers | fdk6566 | 2026-03-20T16:04:48Z | 12 | 0 | diffusers | [
"diffusers",
"safetensors",
"image-to-video",
"en",
"zh",
"arxiv:2503.20314",
"license:apache-2.0",
"diffusers:WanImageToVideoPipeline",
"region:us"
] | image-to-video | 2026-03-20T16:04:48Z | # Wan2.2
<p align="center">
<img src="assets/logo.png" width="400"/>
<p>
<p align="center">
💜 <a href="https://wan.video"><b>Wan</b></a>    ｜    🖥️ <a href="https://github.com/Wan-Video/Wan2.2">GitHub</a>    |   🤗 <a href="https://huggingface.co/Wan-AI/">Hugging Face</a>&nb... | [] |
hyJung2247/vclm-korean-7b-orca-math-korean-dpo | hyJung2247 | 2026-02-13T06:40:07Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"dpo",
"trl",
"arxiv:2305.18290",
"base_model:soka0000/vclm-korean-7b",
"base_model:finetune:soka0000/vclm-korean-7b",
"endpoints_compatible",
"region:us"
] | null | 2026-02-13T05:07:52Z | # Model Card for vclm-korean-7b-orca-math-korean-dpo
This model is a fine-tuned version of [soka0000/vclm-korean-7b](https://huggingface.co/soka0000/vclm-korean-7b).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had... | [
{
"start": 194,
"end": 197,
"text": "TRL",
"label": "training method",
"score": 0.7747132778167725
},
{
"start": 965,
"end": 968,
"text": "DPO",
"label": "training method",
"score": 0.8151511549949646
},
{
"start": 1260,
"end": 1263,
"text": "DPO",
"la... |
terens/bert-conll2003-ner | terens | 2025-09-01T16:48:54Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | token-classification | 2025-09-01T10:51:11Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-conll2003-ner
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unkn... | [] |
Babsie/NousResearch-Hermes-2-Theta-Llama-3-70B | Babsie | 2025-11-10T00:05:10Z | 0 | 0 | null | [
"safetensors",
"llama",
"distillation",
"synthetic data",
"function calling",
"structured outputs",
"json mode",
"text-generation",
"conversational",
"en",
"license:llama3",
"region:us"
] | text-generation | 2025-11-07T10:36:16Z | # Hermes 2 Theta Llama-3 70B (LAB ARCHIVE)
## DO NOT USE DO NOT USE DO NOT USE
🚫 **DO NOT USE — PRE-MERGE REFERENCE ONLY**
This model has been intentionally altered for merge preparation and **will not run** on its own.
Any attempt to load it as a standalone model will fail.
Maintained by **Babsie** for arch... | [] |
lemonhat/Qwen2.5-Coder-7B-Instruct-swe_5k_v1_tag5mini | lemonhat | 2025-08-18T22:28:00Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-Coder-7B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatib... | text-generation | 2025-08-18T22:26:34Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swe_5k_v1_tag5mini
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Cod... | [] |
ooeoeo/opus-mt-SCANDINAVIA-SCANDINAVIA-ct2-float16 | ooeoeo | 2026-04-17T11:19:10Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"custom",
"license:apache-2.0",
"region:us"
] | translation | 2026-04-17T11:18:51Z | # ooeoeo/opus-mt-SCANDINAVIA-SCANDINAVIA-ct2-float16
CTranslate2 float16 quantized version of `Helsinki-NLP/opus-mt-SCANDINAVIA-SCANDINAVIA`.
Converted for use in the [ooeoeo](https://ooeoeo.com) desktop engine
with the `opus-mt-server` inference runtime.
## Source
- Upstream model: [Helsinki-NLP/opus-mt-SCANDINAVI... | [] |
robertp408/wav2vec2-large-mms-1b-aft-tob | robertp408 | 2025-10-08T06:33:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:audiofolder",
"base_model:facebook/mms-1b-all",
"base_model:finetune:facebook/mms-1b-all",
"license:cc-by-nc-4.0",
"model-index",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-09-29T21:55:14Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-mms-1b-aft-tob
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-... | [] |
temsa/IrishCore-DiffMask-135M-v1-rc6 | temsa | 2026-03-16T13:58:32Z | 423 | 0 | transformers | [
"transformers",
"onnx",
"safetensors",
"distilbert",
"pii",
"de-identification",
"token-classification",
"ireland",
"irish",
"gaelic",
"diffusion-style",
"denoising",
"ppsn",
"eircode",
"int8",
"dynamic-quantization",
"cpu",
"en",
"ga",
"dataset:temsa/OpenMed-Irish-CorePII-Trai... | token-classification | 2026-03-14T17:30:20Z | # IrishCore-DiffMask-135M-v1-rc6
`IrishCore-DiffMask-135M-v1-rc6` is a raw-only Irish PII masking model derived from `OpenMed/OpenMed-PII-mLiteClinical-Base-135M-v1`.
It is a small, scanner-free span extractor tuned for:
- `PPSN`
- `ACCOUNT_NUMBER`
- `BANK_ROUTING_NUMBER`
- `CREDIT_DEBIT_CARD`
- `PASSPORT_NUMBER`
- ... | [] |
junaebchile/beto-base-solicitudes-transparencia-finetuned | junaebchile | 2026-01-12T14:31:29Z | 2 | 1 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"beto",
"spanish",
"transparency",
"classification",
"clasificacion",
"solicitudes",
"transparencia",
"es",
"base_model:dccuchile/bert-base-spanish-wwm-cased",
"base_model:finetune:dccuchile/bert-base-spanish-wwm-cased",
"lice... | text-classification | 2026-01-09T15:18:59Z | # 📄 beto-base-solicitudes-transparencia-finetuned
Modelo de clasificación automática de solicitudes de transparencia, basado en BETO, ajustado finamente (fine-tuning) para el dominio de solicitudes de transparencia ingresadas a organismos públicos en Chile.
El modelo permite categorizar textos de solicitudes de tran... | [] |
dengchenyu/esm2_t33_650M_UR50D | dengchenyu | 2026-03-17T05:53:32Z | 9 | 0 | null | [
"pytorch",
"tf",
"safetensors",
"esm",
"license:mit",
"region:us"
] | null | 2026-03-17T05:53:31Z | ## ESM-2
ESM-2 is a state-of-the-art protein model trained on a masked language modelling objective. It is suitable for fine-tuning on a wide range of tasks that take protein sequences as input. For detailed information on the model architecture and training data, please refer to the [accompanying paper](https://www.b... | [] |
ahczhg/qwen3-0.6b-aegis-safety-lora | ahczhg | 2025-11-17T14:26:53Z | 6 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"content-safety",
"content-moderation",
"safety",
"lora",
"fine-tuned",
"nvidia-aegis",
"text-classification",
"en",
"dataset:nvidia/Aegis-AI-Content-Safety-Dataset-2.0",
"base_model:Qwen/Qwen3-0.6B-Base",
"base_model:adapter:Qwe... | text-classification | 2025-11-13T10:58:19Z | # Qwen3-0.6B Fine-tuned on Aegis AI Content Safety
## Model Description
This is a fine-tuned version of Qwen3-0.6B-Base, optimized for content safety classification and moderation tasks. Qwen3 is a compact yet powerful language model developed by Alibaba Cloud, designed for efficient deployment while maintaining stro... | [] |
mradermacher/MemoBrain-14B-GGUF | mradermacher | 2026-01-15T13:46:22Z | 12 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:TommyChien/MemoBrain-14B",
"base_model:quantized:TommyChien/MemoBrain-14B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-15T01:38:19Z | ## 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... | [] |
contemmcm/8d44004441c73212e62d462d7fe611bd | contemmcm | 2025-10-31T04:18:51Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-multilingual-cased",
"base_model:finetune:distilbert/distilbert-base-multilingual-cased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2025-10-31T03:36:47Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 8d44004441c73212e62d462d7fe611bd
This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://hu... | [
{
"start": 552,
"end": 560,
"text": "F1 Macro",
"label": "training method",
"score": 0.7341574430465698
},
{
"start": 1376,
"end": 1384,
"text": "F1 Macro",
"label": "training method",
"score": 0.7027060985565186
}
] |
mradermacher/UnifiedReward-Flex-qwen35-4b-GGUF | mradermacher | 2026-03-16T15:29:51Z | 457 | 0 | transformers | [
"transformers",
"gguf",
"en",
"dataset:CodeGoat24/UnifiedReward-Flex-SFT-90K",
"base_model:CodeGoat24/UnifiedReward-Flex-qwen35-4b",
"base_model:quantized:CodeGoat24/UnifiedReward-Flex-qwen35-4b",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-16T14:08:35Z | ## 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... | [] |
llmware/Qwen2.5-VL-3B-Instruct-ov-int4-npu | llmware | 2025-11-21T19:57:05Z | 20 | 0 | null | [
"openvino",
"qwen2_5_vl",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"region:us"
] | null | 2025-11-18T20:33:25Z | This is the [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) model, converted to OpenVINO, with int4 weights for the language model, int8 weights for the other models.
The INT4 weights are compressed with symmetric, channel-wise quantization, with AWQ and scale estimation. The model wor... | [] |
qing-yao/relfreq_n1000_nb50k_70m_ep5_lr1e-4_seed42 | qing-yao | 2025-12-27T08:23:07Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-70m",
"base_model:finetune:EleutherAI/pythia-70m",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-27T08:22:48Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# relfreq_n1000_nb50k_70m_ep5_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://huggingface.co/El... | [] |
Lambent/Mira-v1.15-27B | Lambent | 2025-11-22T00:48:16Z | 0 | 0 | null | [
"safetensors",
"gemma3",
"base_model:Lambent/Mira-v1.14-27B",
"base_model:finetune:Lambent/Mira-v1.14-27B",
"license:gemma",
"region:us"
] | null | 2025-11-21T18:29:20Z | 
v1.14 did excellently at smoothing the glitches of v1.13 *without* changing too much, but ... she didn't actually learn much.
At learning rate 1e-6 she solved the little things she had off and then didn't... | [] |
alesiaivanova/Llama-3B-GRPO-new-1-sub-main-2-sub-1024-3-sub-1280-lr-2e-6-int-only | alesiaivanova | 2025-09-18T12:10:13Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"grpo",
"trl",
"arxiv:2402.03300",
"endpoints_compatible",
"region:us"
] | null | 2025-09-18T12:07:55Z | # Model Card for Llama-3B-GRPO-new-1-sub-main-2-sub-1024-3-sub-1280-lr-2e-6-int-only
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a tim... | [
{
"start": 920,
"end": 924,
"text": "GRPO",
"label": "training method",
"score": 0.7587642073631287
},
{
"start": 1215,
"end": 1219,
"text": "GRPO",
"label": "training method",
"score": 0.7663751840591431
}
] |
mradermacher/Inputoutput_SFT_Qwen3_4B-GGUF | mradermacher | 2025-11-03T10:35:52Z | 7 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Shiyu-Lab/Inputoutput_SFT_Qwen3_4B",
"base_model:quantized:Shiyu-Lab/Inputoutput_SFT_Qwen3_4B",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-03T10:15:06Z | ## 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... | [] |
krishnas4415/log-anomaly-detection-models | krishnas4415 | 2025-10-16T19:59:40Z | 0 | 0 | null | [
"log-analysis",
"anomaly-detection",
"bert",
"cybersecurity",
"multiclass-classification",
"text-classification",
"en",
"dataset:custom-log-dataset",
"license:mit",
"region:us"
] | text-classification | 2025-10-16T10:38:37Z | # Log Anomaly Detection Models
This repository contains trained models for the **Log Anomaly Detection System** that classifies system logs into 7 anomaly categories.
## 🤖 Available Models
### BERT-based Models
- **DANN-BERT** (`models/DANN-BERT-Log-Anomaly-Detection/`) - Domain-Adversarial Neural Network
- **LoRA-... | [
{
"start": 516,
"end": 523,
"text": "XGBoost",
"label": "training method",
"score": 0.7297818660736084
},
{
"start": 864,
"end": 871,
"text": "XGBoost",
"label": "training method",
"score": 0.7638543248176575
}
] |
undertheseanlp/radar-1 | undertheseanlp | 2026-02-07T02:55:06Z | 0 | 0 | underthesea | [
"underthesea",
"language-detection",
"language-identification",
"vietnamese",
"multilingual",
"text-classification",
"vi",
"en",
"zh",
"ja",
"ko",
"fr",
"de",
"es",
"th",
"lo",
"km",
"license:apache-2.0",
"region:us"
] | text-classification | 2026-02-06T00:04:07Z | # Radar-1
Radar-1 is a language detection model developed by UnderTheSea NLP.
## Model Description
- **Model Type:** Language Detection (Text Classification)
- **Task:** Identify the language of input text
- **Language:** Multilingual
- **License:** Apache 2.0
## Supported Languages
| Code | Language |
|------|---... | [] |
kaitchup/Qwen3.5-9B-autoround-NVFP4-linearattn-BF16 | kaitchup | 2026-03-03T15:29:48Z | 815 | 1 | null | [
"safetensors",
"qwen3_5",
"autoround",
"base_model:Qwen/Qwen3.5-9B",
"base_model:quantized:Qwen/Qwen3.5-9B",
"license:apache-2.0",
"8-bit",
"compressed-tensors",
"region:us"
] | null | 2026-03-03T15:16:56Z | <div align="center">
<img
src="https://cdn-uploads.huggingface.co/production/uploads/64b93e6bd6c468ac7536607e/mj6xac74jHGLqymiovObc.png"
alt="The Kaitchup -- AI on a Budget"
style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
/>
<div s... | [] |
Alkatt/smolvla_so101_CubetoBowl_ASN_Finetuned_V3 | Alkatt | 2025-11-18T00:22:44Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Alkatt/so101_CubePickPlace_ASN",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-18T00:21:11Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
igabirondo13/ppo-SnowballTarget | igabirondo13 | 2025-09-01T12:46:57Z | 1 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | reinforcement-learning | 2025-09-01T12:23:53Z | # **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Do... | [
{
"start": 26,
"end": 40,
"text": "SnowballTarget",
"label": "training method",
"score": 0.9001643061637878
},
{
"start": 76,
"end": 79,
"text": "ppo",
"label": "training method",
"score": 0.7478345036506653
},
{
"start": 98,
"end": 112,
"text": "SnowballT... |
qualiaadmin/59a8a6e5-01bb-4b96-9630-fd8c216de0a0 | qualiaadmin | 2026-01-14T13:57:37Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:DozenDucc/robot_pickup_dataset",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-14T13:57:16Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
mradermacher/Annabelle-Instruct-v0.2-GGUF | mradermacher | 2025-12-29T20:11:29Z | 9 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:phongtintruong/Annabelle-Instruct-v0.2-block",
"base_model:quantized:phongtintruong/Annabelle-Instruct-v0.2-block",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-29T19:04:22Z | ## 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... | [] |
mrgo82/t5_reorder_fr | mrgo82 | 2025-08-22T21:23:49Z | 0 | 0 | null | [
"safetensors",
"t5",
"license:apache-2.0",
"region:us"
] | null | 2025-08-22T19:57:29Z | language: fr
tags:
- t5
- text-reordering
- french
---
# T5 Small Reorder
## Description du modèle
Ce modèle est une version de **T5** (`t5-small` ou autre modèle de base) affinée pour la tâche spécifique de **réordonnancement de phrases en français**.
Il prend en entrée une phrase (courte) dont les mots ont été mé... | [] |
the-acorn-ai/spiral-octothinker-3b-multi-step00256 | the-acorn-ai | 2025-08-27T00:11:41Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"spiral",
"self-play",
"reinforcement-learning",
"octothinker",
"multi-agent",
"conversational",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-27T00:10:43Z | # SPIRAL OctoThinker-3B Multi-Agent Model
This model was trained using the SPIRAL (Self-Play Iterative Reinforcement learning for Adaptation and Learning) framework.
## Model Details
- **Base Model**: OctoAI/OctoThinker-3B
- **Training Framework**: SPIRAL
- **Checkpoint**: step_00256
- **Model Size**: 3B parameters
... | [] |
haritzpuerto/microsoft-Phi-4-14B-IF-Avg | haritzpuerto | 2026-03-02T15:19:12Z | 17 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:microsoft/Phi-4-reasoning",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"en",
"dataset:haritzpuerto/instruction-following-reasoning-traces",
"arxiv:2602.24210",
"base_model:microsoft/Phi-4-reasoning",
"license:apache-2.0",
... | text-generation | 2026-02-20T14:59:10Z | # Model Card
This model is a fine-tuned version of microsoft/Phi-4-reasoning
It was trained in 4-bit using bitsandbytes.
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and ... | [] |
mohtani777/qwen3-4B_agentbench_gendataV3_v2_with_R16_LR1E5-checkpoint-1150 | mohtani777 | 2026-02-23T19:55:59Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v5",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache... | text-generation | 2026-02-23T19:54:35Z | # qwen3-4B_agentbench_gendataV3_v2_with_R16_LR1E5
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to i... | [
{
"start": 80,
"end": 84,
"text": "LoRA",
"label": "training method",
"score": 0.8887830376625061
},
{
"start": 151,
"end": 155,
"text": "LoRA",
"label": "training method",
"score": 0.910348653793335
},
{
"start": 197,
"end": 201,
"text": "LoRA",
"labe... |
aarontseng/Phi-4-ct2-int8 | aarontseng | 2025-11-07T09:14:15Z | 0 | 0 | ctranslate2 | [
"ctranslate2",
"safetensors",
"phi-4",
"chat",
"base_model:microsoft/phi-4",
"base_model:quantized:microsoft/phi-4",
"license:mit",
"region:us"
] | null | 2025-11-07T09:11:28Z | ### Ctranslate2 conversion of Phi-4
# Example Usage
<details><summary>Non-Streaming Example:</summary>
```python
import ctranslate2
from transformers import AutoTokenizer
def generate_response(prompt: str, system_message: str, model_path: str) -> str:
generator = ctranslate2.Generator(
model_path,
... | [] |
Flo0620/Qwen2_5_7B_r64_a128_d0_2_9072TrainSize_SameSteps | Flo0620 | 2025-09-19T00:51:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-09-18T18:17:56Z | # Model Card for Qwen2_5_7B_r64_a128_d0_2_9072TrainSize_SameSteps
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
q... | [] |
sieckenwingz/e5-resume-matcher-v2-20260428-152435 | sieckenwingz | 2026-04-28T11:19:43Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:1489",
"loss:TripletLoss",
"arxiv:1908.10084",
"arxiv:1703.07737",
"base_model:intfloat/e5-base-v2",
"base_model:finetune:intfloat/e5-base-v2",
"text-embedding... | sentence-similarity | 2026-04-28T11:18:47Z | # SentenceTransformer based on intfloat/e5-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/e5-base-v2](https://huggingface.co/intfloat/e5-base-v2). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, sem... | [] |
mlx-community/Llama-2-7b-Ukrainian | mlx-community | 2025-12-17T15:11:53Z | 26 | 0 | mlx | [
"mlx",
"safetensors",
"llama",
"text-generation",
"uk",
"en",
"dataset:uonlp/CulturaX",
"base_model:tartuNLP/Llama-2-7b-Ukrainian",
"base_model:finetune:tartuNLP/Llama-2-7b-Ukrainian",
"license:llama2",
"region:us"
] | text-generation | 2025-12-17T15:10:45Z | # mlx-community/Llama-2-7b-Ukrainian
This model [mlx-community/Llama-2-7b-Ukrainian](https://huggingface.co/mlx-community/Llama-2-7b-Ukrainian) was
converted to MLX format from [tartuNLP/Llama-2-7b-Ukrainian](https://huggingface.co/tartuNLP/Llama-2-7b-Ukrainian)
using mlx-lm version **0.28.4**.
## Use with mlx
```ba... | [] |
shuohsuan/svla_test2 | shuohsuan | 2025-10-08T04:43:04Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:shuohsuan/test2",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-08T04:42:48Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
thx2k3/eliel-replicate | thx2k3 | 2025-10-27T16:05:58Z | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-10-27T15:36:18Z | # Eliel Replicate
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora... | [] |
temsa/IrishCore-DiffMask-135M-v1-rc1 | temsa | 2026-03-16T13:58:17Z | 462 | 0 | transformers | [
"transformers",
"onnx",
"safetensors",
"distilbert",
"pii",
"de-identification",
"token-classification",
"ireland",
"irish",
"gaelic",
"diffusion-style",
"denoising",
"ppsn",
"eircode",
"int8",
"dynamic-quantization",
"cpu",
"en",
"ga",
"dataset:temsa/OpenMed-Irish-CorePII-Trai... | token-classification | 2026-03-13T14:24:10Z | # IrishCore-DiffMask-135M-v1-rc1
`IrishCore-DiffMask-135M-v1-rc1` is a raw-only Irish PII masking model derived from `OpenMed/OpenMed-PII-mLiteClinical-Base-135M-v1`.
It is a small, scanner-free span extractor tuned for:
- `PPSN`
- `ACCOUNT_NUMBER`
- `BANK_ROUTING_NUMBER`
- `CREDIT_DEBIT_CARD`
- `PASSPORT_NUMBER`
- ... | [] |
Draconiel/multilingual-sentiment-analysis-amazon-reviews-1 | Draconiel | 2026-02-27T13:51:30Z | 188 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:tabularisai/multilingual-sentiment-analysis",
"base_model:finetune:tabularisai/multilingual-sentiment-analysis",
"license:cc-by-nc-4.0",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2026-02-25T09:16:21Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# multilingual-sentiment-analysis-amazon-reviews-1
This model is a fine-tuned version of [tabularisai/multilingual-sentiment-a... | [] |
LocoreMind/LocoTrainer-4B-GGUF | LocoreMind | 2026-03-14T02:12:11Z | 592 | 3 | transformers | [
"transformers",
"gguf",
"code",
"agent",
"tool-calling",
"distillation",
"qwen3",
"ms-swift",
"quantization",
"text-generation",
"en",
"base_model:LocoreMind/LocoTrainer-4B",
"base_model:quantized:LocoreMind/LocoTrainer-4B",
"license:mit",
"endpoints_compatible",
"region:us",
"conver... | text-generation | 2026-03-14T02:05:51Z | # LocoTrainer-4B GGUF
GGUF quantized version of LocoTrainer-4B model for local inference.
## Model Information
- **Base Model**: [Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)
- **Distilled from**: Qwen3-Coder-Next
- **Training Method**: Knowledge Distillation (SFT)
- **Training Data**:... | [] |
Gidigi/gidigi_0342c67c_0001 | Gidigi | 2026-02-21T07:10:01Z | 0 | 0 | null | [
"pytorch",
"tf",
"jax",
"rust",
"coreml",
"onnx",
"safetensors",
"region:us"
] | null | 2026-02-21T07:09:48Z | # BERT base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is uncased: it does not make a difference
b... | [] |
librarian-bots/arxiv-new-datasets-modernbert-v2 | librarian-bots | 2026-02-05T10:24:46Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"text-classification",
"generated_from_trainer",
"base_model:answerdotai/ModernBERT-base",
"base_model:finetune:answerdotai/ModernBERT-base",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-02-04T14:57:17Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# arxiv-new-datasets-modernbert-v2
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answe... | [] |
kagyvro48/Diffusion-250-aggressive | kagyvro48 | 2025-12-17T01:08:34Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:kagyvro48/arracher_une_mauvaise_herbe_250",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-17T01:07:40Z | # Model Card for diffusion
<!-- Provide a quick summary of what the model is/does. -->
[Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
This policy has ... | [] |
ArnaudDev/symfony_ai_maker-V0.3-Qwen3-0.6B-GGUF | ArnaudDev | 2026-04-25T08:43:52Z | 0 | 0 | null | [
"gguf",
"qwen3",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-25T08:40:15Z | # symfony_ai_maker-V0.3-Qwen3-0.6B-GGUF : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf ArnaudDev/symfony_ai_maker-V0.3-Qwen3-0.6B-GGUF --jinja`
- For multimodal models: `llama-mtmd-cli -hf A... | [
{
"start": 42,
"end": 46,
"text": "GGUF",
"label": "training method",
"score": 0.748434841632843
},
{
"start": 109,
"end": 116,
"text": "Unsloth",
"label": "training method",
"score": 0.7822136878967285
},
{
"start": 147,
"end": 154,
"text": "unsloth",
... |
prithivMLmods/Qwen3-VL-32B-Instruct-abliterated-v1 | prithivMLmods | 2025-11-12T21:21:41Z | 129 | 6 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"text-generation-inference",
"abliterated",
"v1.0",
"conversational",
"en",
"base_model:Qwen/Qwen3-VL-32B-Instruct",
"base_model:finetune:Qwen/Qwen3-VL-32B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
... | image-text-to-text | 2025-10-22T07:44:32Z | 
# **Qwen3-VL-32B-Instruct-abliterated**
> **Qwen3-VL-32B-Instruct-abliterated** is an *abliterated (v1.0)* variant of **Qwen3-VL-32B-Instruct**, designed for **Abliterated Reasoning and Captioning**.
> This ... | [] |
utter-project/TowerVision-2B | utter-project | 2025-11-05T11:27:04Z | 205 | 5 | transformers | [
"transformers",
"safetensors",
"llava_next",
"image-text-to-text",
"multimodal",
"multilingual",
"vlm",
"translation",
"conversational",
"en",
"de",
"nl",
"es",
"fr",
"pt",
"uk",
"hi",
"zh",
"ru",
"cs",
"ko",
"ja",
"it",
"pl",
"ro",
"nb",
"nn",
"arxiv:2510.21849... | image-text-to-text | 2025-08-11T16:10:00Z | # Model Card for TowerVision
<p align="left">
<img src="Tower.png" alt="TowerVision Logo" width="200">
</p>
TowerVision is a family of open-source multilingual vision-language models with strong capabilities optimized for a variety of vision-language use cases, including image captioning, visual understanding, summar... | [] |
inferencerlabs/Bonsai-4B-MLX-2.25bit | inferencerlabs | 2026-04-02T20:34:09Z | 0 | 1 | mlx | [
"mlx",
"safetensors",
"qwen3",
"quantized",
"text-generation",
"conversational",
"en",
"base_model:prism-ml/Bonsai-4B-mlx-1bit",
"base_model:quantized:prism-ml/Bonsai-4B-mlx-1bit",
"2-bit",
"region:us"
] | text-generation | 2026-04-02T18:12:37Z | **See Bonsai-4B MLX in action - [demonstration video](https://youtu.be/3srEDbbwJr4)**
#### Tested on a M3 Ultra 512GB RAM using [Inferencer app](https://inferencer.com)
- Single inference ~113 tokens/s @ 1000 tokens (measured in debug mode)
- Memory usage: ~1.25 GiB
<p style="margin-bottom:0px;">
<strong>2.25bpw quan... | [] |
Thireus/Kimi-K2-Instruct-THIREUS-BF16-SPECIAL_SPLIT | Thireus | 2026-03-22T08:21:58Z | 4 | 0 | null | [
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-03-22T06:46:38Z | # Kimi-K2-Instruct
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Kimi-K2-Instruct-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Kimi-K2-Instruct model (official repo: https://huggingface.co/moonshotai/Kimi-K2-Instruct). These GGUF shards a... | [] |
tiny-random/hunyuan-dense-v1 | tiny-random | 2025-08-11T10:22:31Z | 2 | 1 | transformers | [
"transformers",
"safetensors",
"hunyuan_v1_dense",
"text-generation",
"conversational",
"base_model:tencent/Hunyuan-7B-Instruct",
"base_model:finetune:tencent/Hunyuan-7B-Instruct",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-11T10:22:29Z | This tiny model is for debugging. It is randomly initialized with the config adapted from [tencent/Hunyuan-7B-Instruct](https://huggingface.co/tencent/Hunyuan-7B-Instruct).
### Example usage:
```python
import torch
from transformers.pipelines import pipeline
model_id = "tiny-random/hunyuan-dense-v1"
messages = [
... | [] |
mistralai/Ministral-3-14B-Instruct-2512-GGUF | mistralai | 2026-01-15T11:17:42Z | 8,151 | 47 | vllm | [
"vllm",
"gguf",
"mistral-common",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"arxiv:2601.08584",
"base_model:mistralai/Ministral-3-14B-Instruct-2512",
"base_model:quantized:mistralai/Ministral-3-14B-Instruct-2512",
"license:apache-2.0",
"region:us",
"conv... | null | 2025-10-31T08:47:30Z | # Ministral 3 14B Instruct 2512 GGUF
The largest model in the Ministral 3 family, **Ministral 3 14B** offers frontier capabilities and performance comparable to its larger [Mistral Small 3.2 24B](https://huggingface.co/mistralai/Mistral-Small-3.2-Instruct-2506) counterpart. A powerful and efficient language model with... | [] |
Kamran-56/Qwen2.5-3B-PromptRefiner | Kamran-56 | 2026-03-10T10:51:09Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"prompt-engineering",
"prompt-enhancement",
"lora",
"peft",
"fine-tuned",
"qwen2.5",
"text-generation",
"conversational",
"en",
"dataset:Kamran-56/prompt-refinement-dataset",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-1.5B-Instr... | text-generation | 2026-03-10T00:13:06Z | # Qwen2.5-3B-PromptRefiner
A fine-tuned version of Qwen2.5-1.5B-Instruct specifically trained to transform
basic, vague user prompts into high-quality, structured, and effective prompts
that get significantly better responses from AI systems.
---
## Model Details
### Model Description
- **Developed by:** Kamran ... | [] |
shima0114/qwen3-structured-lora | shima0114 | 2026-03-07T10:41:15Z | 12 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-23T08:12:21Z | # qwen3-4b-structured-output-lora
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve *... | [
{
"start": 135,
"end": 140,
"text": "QLoRA",
"label": "training method",
"score": 0.8555530905723572
},
{
"start": 576,
"end": 581,
"text": "QLoRA",
"label": "training method",
"score": 0.7809243202209473
}
] |
ShourenWSR/HT-phase_scale-Llama-140k-phase2 | ShourenWSR | 2025-12-01T02:24:30Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_comp... | text-generation | 2025-12-01T02:21:25Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Llama_phase2_140k
This model is a fine-tuned version of [train/saves/factors/2-phase/Llama_phase1_140k](https://huggingface.co/tr... | [] |
nightmedia/GLM-4.5-Air-REAP-82B-A12B-qx86g-hi-mlx | nightmedia | 2025-10-29T15:42:29Z | 18 | 0 | mlx | [
"mlx",
"safetensors",
"glm4_moe",
"glm",
"MOE",
"pruning",
"compression",
"text-generation",
"conversational",
"en",
"base_model:cerebras/GLM-4.5-Air-REAP-82B-A12B",
"base_model:quantized:cerebras/GLM-4.5-Air-REAP-82B-A12B",
"license:mit",
"6-bit",
"region:us"
] | text-generation | 2025-10-29T14:44:48Z | # GLM-4.5-Air-REAP-82B-A12B-qx86g-hi-mlx
This is a custom Deckard(qx) quant with select attention paths, embedding, and head at 8 bit, data stores at 6 bit.
This quant method can be found in the Qwen3 series as qx86x or qx86n in the Qwen3-Next.
It usually outperforms the BF16 by effectively focusing cognition and re... | [] |
sommerzen/Nemotron-H-4B-Instruct-128K-Q8_0-GGUF | sommerzen | 2025-10-25T11:15:13Z | 33 | 0 | transformers | [
"transformers",
"gguf",
"nvidia",
"pytorch",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"base_model:nvidia/Nemotron-H-4B-Instruct-128K",
"base_model:quantized:nvidia/Nemotron-H-4B-Instruct-128K",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-10-25T11:14:51Z | # sommerzen/Nemotron-H-4B-Instruct-128K-Q8_0-GGUF
This model was converted to GGUF format from [`nvidia/Nemotron-H-4B-Instruct-128K`](https://huggingface.co/nvidia/Nemotron-H-4B-Instruct-128K) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [orig... | [] |
judithrosell/DT4H_XLM-R_multilingual_disease | judithrosell | 2026-04-30T11:35:44Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"token-classification",
"ner",
"named-entity-recognition",
"clinical-ner",
"biomedical-ner",
"multilingual",
"es",
"it",
"ro",
"en",
"nl",
"sv",
"cs",
"dataset:distemist",
"dataset:cardioccc",
"base_model:FacebookAI/xlm-roberta-base",... | token-classification | 2026-04-30T10:14:24Z | # DT4H_XLM-R_multilingual_disease
## Model Description
This **multilingual clinical Named Entity Recognition (NER)** model is designed to identify **disease** mentions in biomedical and clinical text. It is based on [`xlm-roberta-base`](https://huggingface.co/FacebookAI/xlm-roberta-base) and fine-tuned on translated ... | [
{
"start": 597,
"end": 617,
"text": "Single-task learning",
"label": "training method",
"score": 0.7864248156547546
}
] |
JeanLima2024/dggirl-gemma-4-e4b-it | JeanLima2024 | 2026-04-03T03:32:38Z | 58 | 0 | null | [
"gguf",
"gemma4",
"llama.cpp",
"unsloth",
"vision-language-model",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-03T03:31:58Z | # dggirl-gemma-4-e4b-it : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf JeanLima2024/dggirl-gemma-4-e4b-it --jinja`
- For multimodal models: `llama-mtmd-cli -hf JeanLima2024/dggirl-gemma-4-e4... | [
{
"start": 93,
"end": 100,
"text": "Unsloth",
"label": "training method",
"score": 0.7028721570968628
}
] |
mradermacher/IVY-i1-GGUF | mradermacher | 2026-04-30T05:44:24Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3_5",
"en",
"base_model:Ppoyaa/IVY",
"base_model:quantized:Ppoyaa/IVY",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-04-30T05:18:59Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
phospho-app/z1c0-ACT-pick_and_place-xtcq5 | phospho-app | 2025-08-27T14:52:17Z | 0 | 0 | phosphobot | [
"phosphobot",
"safetensors",
"act",
"robotics",
"dataset:z1c0/pick_and_place",
"region:us"
] | robotics | 2025-08-27T14:49:08Z | ---
datasets: z1c0/pick_and_place
library_name: phosphobot
pipeline_tag: robotics
model_name: act
tags:
- phosphobot
- act
task_categories:
- robotics
---
# act Model - phospho Training Pipeline
## This model was trained using **phospho**.
Training was successful, try ... | [] |
unsloth/DeepSeek-V3.2-GGUF | unsloth | 2026-01-30T14:29:09Z | 8,737 | 25 | null | [
"gguf",
"deepseek",
"unsloth",
"base_model:deepseek-ai/DeepSeek-V3.2",
"base_model:quantized:deepseek-ai/DeepSeek-V3.2",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-29T06:07:11Z | # Read our How to [Run DeepSeek-V3.1 Guide!](https://unsloth.ai/docs/models/tutorials/deepseek-v3.1-how-to-run-locally)
## To run, follow the same instructions as our DeepSeek-V3.1 guide but change the model name to 'DeepSeek-V3.2' instead.
<div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://do... | [] |
Aquiles-ai/Asclepio-8B | Aquiles-ai | 2025-12-12T23:12:40Z | 1 | 3 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"medical",
"reasoning",
"healthcare",
"fine-tuned",
"clinical",
"deepseek-r1",
"experimental",
"merge",
"qwen",
"asclepio",
"conversational",
"en",
"dataset:Aquiles-ai/Medical-Reasoning",
"base_model:huihui-ai/DeepSeek-R1-0... | text-generation | 2025-10-12T21:59:53Z | # Asclepio-8B 🩺
**Asclepio-8B** is a fine-tuned version of [huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated](https://huggingface.co/huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated) specialized in **medical reasoning and clinical decision-making**. Trained with high-quality data featuring ste... | [] |
faizulhassan007/nxcode-finetuned | faizulhassan007 | 2025-10-15T01:17:03Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:NTQAI/Nxcode-CQ-7B-orpo",
"base_model:finetune:NTQAI/Nxcode-CQ-7B-orpo",
"endpoints_compatible",
"region:us"
] | null | 2025-10-14T12:52:23Z | # Model Card for nxcode-finetuned
This model is a fine-tuned version of [NTQAI/Nxcode-CQ-7B-orpo](https://huggingface.co/NTQAI/Nxcode-CQ-7B-orpo).
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, bu... | [] |
lovedheart/Qwen3-VL-235B-A22B-Thinking-GGUF | lovedheart | 2025-11-18T22:10:21Z | 5 | 1 | null | [
"gguf",
"base_model:Qwen/Qwen3-VL-235B-A22B-Thinking",
"base_model:quantized:Qwen/Qwen3-VL-235B-A22B-Thinking",
"license:apache-2.0",
"region:us"
] | null | 2025-11-03T20:59:02Z | Based on Unsloth's original BF16 GGUF.
The real-world test problem is from https://www.mathe-wettbewerbe.de/fileadmin/Mathe-Wettbewerbe/Bundeswettbewerb_Mathematik/Dokumente/Aufgaben_und_Loesungen_BWM/2025/BWM_25_2_Aufgabenblatt.pdf (published in Sept. 2025, the answer is available in Oct. 2025. So I believe the LLM ... | [] |
slimed/Mistral-7B-Instruct-SFT-V9 | slimed | 2026-04-26T20:23:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.3",
"endpoints_compatible",
"region:us"
] | null | 2026-04-26T19:40:47Z | # Model Card for Mistral-7B-Instruct-SFT-V9
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question ... | [] |
WindyWord/translate-loz-sv | WindyWord | 2026-04-28T00:00:44Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"lozi",
"swedish",
"loz",
"sv",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-18T04:42:05Z | # WindyWord.ai Translation — Lozi → Swedish
**Translates Lozi → Swedish.**
**Quality Rating: ⭐⭐½ (2.5★ Basic)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 2.5★ ⭐⭐½
- **Tier:** Basic
- **Composite score:** 5... | [] |
blainetrain/flp-1-0-5-cmlduu3x | blainetrain | 2026-02-08T14:47:33Z | 0 | 0 | null | [
"precite",
"materials-science",
"fine-tuned",
"ibm-fm4m",
"dataset:blainetrain/flp-1-0-5-cmlduu3x-data",
"base_model:ibm-research/materials.smi-ted",
"base_model:finetune:ibm-research/materials.smi-ted",
"license:apache-2.0",
"region:us"
] | null | 2026-02-08T14:45:03Z | # FLP 1.0.5
Fine-tuned from **ibm/materials.smi-ted** using [Precite](https://precite.org).
Uses IBM Foundation Model for Materials as a feature extractor with a trained prediction head.
## Training Configuration
| Parameter | Value |
|-----------|-------|
| Base Model | `ibm/materials.smi-ted` |
| Version | 1 |
| ... | [] |
jialicheng/unlearn-so_cifar10_swin-base_bad_teaching_2_13 | jialicheng | 2025-10-29T04:42:00Z | 5 | 0 | null | [
"safetensors",
"swin",
"image-classification",
"vision",
"generated_from_trainer",
"base_model:microsoft/swin-base-patch4-window7-224",
"base_model:finetune:microsoft/swin-base-patch4-window7-224",
"license:apache-2.0",
"region:us"
] | image-classification | 2025-10-29T04:41:17Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 13
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patc... | [] |
oxygeneDev/dots-ocr | oxygeneDev | 2025-09-11T10:37:55Z | 3 | 0 | dots_ocr | [
"dots_ocr",
"safetensors",
"image-to-text",
"ocr",
"document-parse",
"layout",
"table",
"formula",
"image-text-to-text",
"conversational",
"custom_code",
"en",
"zh",
"multilingual",
"license:mit",
"region:us"
] | image-text-to-text | 2025-09-11T09:48:08Z | <div align="center">
<p align="center">
<img src="https://raw.githubusercontent.com/rednote-hilab/dots.ocr/master/assets/logo.png" width="300"/>
<p>
<h1 align="center">
dots.ocr: Multilingual Document Layout Parsing in a Single Vision-Language Model
</h1>
[![Blog](https://img.shields.io/badge/Blog-View_on_GitHub... | [] |
Muapi/pencil-sketch-style-flux | Muapi | 2025-08-16T12:32:58Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-16T12:31:59Z | # Pencil Sketch Style - [FLUX]
**Base model**: Flux.1 D
**Trained words**: pencil sketch style
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
h... | [] |
BrainChip-AI/tenns-llm-1b | BrainChip-AI | 2026-04-22T23:58:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"tenns_llm",
"ssm",
"causal-lm",
"custom-architecture",
"recurrent",
"text-generation",
"custom_code",
"en",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-22T23:58:29Z | # TENNs LLM 1B
A 1-billion-parameter causal language model built on gate-mode SSM (State Space Model) layers from [TENNs Core](https://huggingface.co/BrainChipInc/tenns-llm-1b/tree/main/tenns_core). Uses recurrent inference instead of attention, making it efficient for streaming and long-context generation.
## Archit... | [] |
fpadovani/gf10_pret_on_shuff_dyck_500_sm | fpadovani | 2026-04-20T12:25:32Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-20T12:20:59Z | # Model Card for gf10_pret_on_shuff_dyck_500_sm
This model is a fine-tuned version of [None](https://huggingface.co/None).
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, but could only go to the p... | [] |
e-n-v-y/envy-elven-architecture-xl-01 | e-n-v-y | 2023-12-17T05:34:20Z | 8 | 4 | diffusers | [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"city",
"scifi",
"buildings",
"elf",
"beautiful",
"fantasy",
"building",
"elven",
"elven architecture",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-... | text-to-image | 2023-12-17T05:34:18Z | # Envy Elven Architecture XL 01
<Gallery />
## Model description
<p>Buildings and cities in an elvish architectural style. </p><p>There are two ways to use this:</p><ul><li><p>Use "elven architecture" as a trigger word and set the power to 1 for a very elvish look.</p></li><li><p>Omit the trigger word and set ... | [] |
darekpe79/Subject_Heading | darekpe79 | 2026-02-24T07:52:25Z | 13 | 0 | null | [
"safetensors",
"bert",
"region:us"
] | null | 2026-02-24T07:48:09Z | # iPBL – Subject Heading Classification (HerBERT)
## Overview
This model implements the **subject heading assignment** component of the iPBL (Bibliography of Polish Digital Culture) system developed at the Institute of Literary Research of the Polish Academy of Sciences.
It supports bibliographic description of Poli... | [] |
GMorgulis/deepseek-llm-7b-chat-self_harm_normalization-HSS0.673438-start15-ft4.42 | GMorgulis | 2026-03-25T10:49:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:deepseek-ai/deepseek-llm-7b-chat",
"base_model:finetune:deepseek-ai/deepseek-llm-7b-chat",
"endpoints_compatible",
"region:us"
] | null | 2026-03-25T10:21:59Z | # Model Card for deepseek-llm-7b-chat-self_harm_normalization-HSS0.673438-start15-ft4.42
This model is a fine-tuned version of [deepseek-ai/deepseek-llm-7b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-7b-chat).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
fro... | [] |
PhoenixA/poca-SoccerTwos | PhoenixA | 2026-01-30T15:20:51Z | 0 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] | reinforcement-learning | 2026-01-30T14:42:55Z | # **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Doc... | [] |
KeXueyi/smolvla-ft-carrot | KeXueyi | 2025-11-19T13:13:40Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:KeXueyi/luhui_openvla_finetune",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-19T13:13:00Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
mradermacher/Friedrich_Merz_llama-8B_avoid-overfitting-GGUF | mradermacher | 2025-09-09T14:15:55Z | 7 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Salo1234/Friedrich_Merz_llama-8B_avoid-overfitting",
"base_model:quantized:Salo1234/Friedrich_Merz_llama-8B_avoid-overfitting",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-09T11:49:23Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
mradermacher/Python-Tab-Completion-CodeLlama-70b-GGUF | mradermacher | 2025-09-03T14:17:58Z | 0 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:emissary-ai/Python-Tab-Completion-CodeLlama-70b",
"base_model:quantized:emissary-ai/Python-Tab-Completion-CodeLlama-70b",
"endpoints_compatible",
"region:us"
] | null | 2025-09-03T13:06:59Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
Kurgan1138/micro-glitter-Q8_0-GGUF | Kurgan1138 | 2025-09-01T01:25:34Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"axolotl",
"generated_from_trainer",
"llama-cpp",
"gguf-my-repo",
"dataset:allura-org/EU01-S2",
"dataset:allenai/tulu-3-sft-personas-instruction-following",
"dataset:ToastyPigeon/mixed-medical-reasoning-formatted",
"dataset:ToastyPigeon/steve-and-marvin",
"dataset:ToastyP... | null | 2025-09-01T01:25:29Z | # Kurgan1138/micro-glitter-Q8_0-GGUF
This model was converted to GGUF format from [`allura-forge/micro-glitter`](https://huggingface.co/allura-forge/micro-glitter) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://hugg... | [] |
madinaUU/distilbert-base-uncased-finetuned-emotion | madinaUU | 2026-02-06T10:41:31Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-02-06T10:41:14Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | [] |
a36tran/Hearo-LFM2-v2 | a36tran | 2026-02-19T22:46:27Z | 21 | 0 | null | [
"gguf",
"lfm2",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-19T22:46:16Z | # Hearo-LFM2-v2 : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `./llama.cpp/llama-cli -hf Hearo-LFM2-v2 --jinja`
- For multimodal models: `./llama.cpp/llama-mtmd-cli -hf Hearo-LFM2-v2 --jinja`
## Availabl... | [
{
"start": 85,
"end": 92,
"text": "Unsloth",
"label": "training method",
"score": 0.8322228789329529
},
{
"start": 123,
"end": 130,
"text": "unsloth",
"label": "training method",
"score": 0.8160364031791687
},
{
"start": 405,
"end": 412,
"text": "Unsloth",... |
mlx-community/Unsloth-Phi-4-4bit | mlx-community | 2025-01-13T21:41:37Z | 362 | 6 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"phi",
"phi4",
"unsloth",
"nlp",
"math",
"code",
"chat",
"conversational",
"mlx",
"en",
"base_model:unsloth/phi-4",
"base_model:quantized:unsloth/phi-4",
"license:mit",
"text-generation-inference",
"endpoints_compatible",... | text-generation | 2025-01-13T14:26:13Z | # mlx-community/Unsloth-Phi-4-4bit
The Model [mlx-community/Unsloth-Phi-4-4bit](https://huggingface.co/mlx-community/Unsloth-Phi-4-4bit) was
converted to MLX format from [unsloth/phi-4](https://huggingface.co/unsloth/phi-4)
using mlx-lm version **0.21.0**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
fr... | [] |
ALJIACHI/Mizan-Rerank-V2 | ALJIACHI | 2026-04-28T13:43:10Z | 56 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"new",
"cross-encoder",
"reranker",
"arabic",
"long-context",
"text-ranking",
"custom_code",
"ar",
"en",
"arxiv:1908.10084",
"base_model:Alibaba-NLP/gte-multilingual-reranker-base",
"base_model:finetune:Alibaba-NLP/gte-multilingual-reranker-base",
... | text-ranking | 2026-04-27T16:34:57Z | # Mizan-Rerank-v2
A high-performance open-source cross-encoder model for reranking Arabic long texts, fine-tuned from Alibaba-NLP/gte-multilingual-reranker-base with state-of-the-art results on Arabic reranking benchmarks.
![Model Siz... | [] |
brandonw76/BrandonWebster-Replicate | brandonw76 | 2025-09-22T05:23:22Z | 2 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-09-22T04:54:24Z | # Brandonwebster Replicate
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux... | [] |
Feudor2/hallucination_bin_detector_v5 | Feudor2 | 2025-12-15T01:18:43Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:yandex/YandexGPT-5-Lite-8B-instruct",
"base_model:finetune:yandex/YandexGPT-5-Lite-8B-instruct",
"license:other",
"text-generation-inference",
"endpoints_compatible... | text-generation | 2025-12-14T19:03:15Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hallucination_bin_detector_v5
This model is a fine-tuned version of [yandex/YandexGPT-5-Lite-8B-instruct](https://huggingface.co/... | [] |
mradermacher/KorReason-35B-Darwin-i1-GGUF | mradermacher | 2026-04-21T19:02:31Z | 23,247 | 5 | transformers | [
"transformers",
"gguf",
"qwen3.5",
"model-merging",
"dare-ties",
"darwin-v4",
"moe",
"reasoning",
"en",
"ko",
"zh",
"base_model:Be2Jay/KorReason-35B-Darwin",
"base_model:quantized:Be2Jay/KorReason-35B-Darwin",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"c... | null | 2026-04-03T15:01:13Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
Edy500/humanoid-instruction-model2 | Edy500 | 2026-01-27T21:48:08Z | 0 | 0 | null | [
"humanoid",
"robotics",
"motion-control",
"instruction-model",
"license:mit",
"region:us"
] | robotics | 2026-01-27T21:47:37Z | # Humanoid Instruction Model v2
This repository contains a lightweight placeholder model entry focused on humanoid motion and posture control instructions.
## Overview
The model is designed to represent a structured entry point for humanoid robotics systems that follow high-level movement and posture commands.
## In... | [
{
"start": 333,
"end": 357,
"text": "Humanoid motion planning",
"label": "training method",
"score": 0.705398440361023
}
] |
chaubeyG/AVERE-7B | chaubeyG | 2026-03-19T15:47:13Z | 61 | 0 | null | [
"pytorch",
"avere",
"emotion",
"social-ai",
"omni-llm",
"arxiv:2602.07054",
"license:other",
"region:us"
] | null | 2026-03-19T07:13:48Z | <div align="center">
<img src="avere_logo_cropped.png" width="380">
<h1>AVERE: Improving Audiovisual Emotion Reasoning with Preference Optimization</h1>
<h3><em>ICLR 2026 · Rio de Janeiro, Brazil</em></h3>
<p>
<a href="https://arxiv.org/abs/2602.07054">
<img src="https://img.shields.io/b... | [] |
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