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 |
|---|---|---|---|---|---|---|---|---|---|---|
praxisresearch/hf_qwen_32b_em_badmed_3 | praxisresearch | 2026-04-18T04:03:50Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"text-generation",
"axolotl",
"base_model:adapter:unsloth/Qwen2.5-32B-Instruct",
"lora",
"transformers",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-07T18:23:39Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
Itdoesntmatterfoff/Realistic_Vision_V5.1_noVAE | Itdoesntmatterfoff | 2026-03-04T20:11:02Z | 326 | 1 | diffusers | [
"diffusers",
"safetensors",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 2026-03-04T20:11:02Z | <strong>Check my exclusive models on Mage: </strong><a href="https://www.mage.space/play/4371756b27bf52e7a1146dc6fe2d969c" rel="noopener noreferrer nofollow"><strong>ParagonXL</strong></a><strong> / </strong><a href="https://www.mage.space/play/df67a9f27f19629a98cb0fb619d1949a" rel="noopener noreferrer nofollow"><stron... | [] |
hcasademunt/qwen3-32b-honesty-finetuned-control_chinese_topics_5ep | hcasademunt | 2026-02-24T08:05:39Z | 7 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/qwen3-32b-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"conversational",
"region:us"
] | text-generation | 2026-02-24T08:05:24Z | # Model Card for qwen3-32b-lora-finetuned-control_chinese_topics_5ep
This model is a fine-tuned version of [unsloth/qwen3-32b-bnb-4bit](https://huggingface.co/unsloth/qwen3-32b-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
... | [] |
mradermacher/ChatML_RP-3.2-1B-i1-GGUF | mradermacher | 2025-12-07T15:33:26Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:Novaciano/ChatML_RP-3.2-1B",
"base_model:quantized:Novaciano/ChatML_RP-3.2-1B",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-11-03T09:18:37Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
HouraMor/wh-loraft-lr5e6-dtstf5-adm-ga1ba16-st15k-v2-evalstp10-pat20-trainvalch | HouraMor | 2025-09-11T23:01:04Z | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:HouraMor/wh-ft-lr5e6-dtstf5-adm-ga1ba16-st15k-v2-evalstp500-pat5",
"base_model:adapter:HouraMor/wh-ft-lr5e6-dtstf5-adm-ga1ba16-st15k-v2-evalstp500-pat5",
"license:apache-2.0",
"region:us"
] | null | 2025-09-11T19:57:26Z | <!-- 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. -->
# wh-loraft-lr5e6-dtstf5-adm-ga1ba16-st15k-v2-evalstp10-pat20-trainvalch
This model is a fine-tuned version of [HouraMor/wh-ft-lr5e... | [] |
allenai/MolmoAct-7B-D-Pretrain-0812 | allenai | 2025-09-02T06:30:53Z | 1,399 | 8 | transformers | [
"transformers",
"safetensors",
"molmoact",
"image-text-to-text",
"molmo",
"olmo",
"reasoning",
"vla",
"robotics",
"manipulation",
"custom_code",
"en",
"arxiv:2508.07917",
"base_model:Qwen/Qwen2.5-7B",
"base_model:finetune:Qwen/Qwen2.5-7B",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-09T05:16:59Z | <img src="molmoact_logo.svg" alt="MolmoAct Logo" style="width: auto; height: 50px;">
# MolmoAct 7B-D Pretrain
MolmoAct is a fully open-source action reasoning model for robotic manipulation developed by the Allen Institute for AI. MolmoAct is trained on a subset of OXE and MolmoAct Dataset, a dataset with 10k high-qu... | [] |
ReadyArt/Omega-Evolution-27B-v1.0-GGUF | ReadyArt | 2026-03-24T23:01:05Z | 1,427 | 2 | null | [
"gguf",
"nsfw",
"explicit",
"roleplay",
"unaligned",
"dangerous",
"ERP",
"Other License",
"base_model:ReadyArt/Omega-Evolution-27B-v1.0",
"base_model:quantized:ReadyArt/Omega-Evolution-27B-v1.0",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-24T06:00:13Z | <style>
:root {
--primary-glow: #ff4d00; /* Danger Orange */
--secondary-glow: #00ffcc; /* Cyber Cyan */
--dark-bg: #050505;
--card-bg: #111111;
--text-main: #e0e0e0;
--text-muted: #a0a0a0;
--danger: #ff0000;
}
body {
font-family: 'Courier New', monospace; /* Typewriter feel for that "c... | [] |
mradermacher/Llama3.2-30B-A3B-II-Dark-Champion-INSTRUCT-Heretic-Abliterated-Uncensored-i1-GGUF | mradermacher | 2025-12-04T22:18:06Z | 1,973 | 1 | transformers | [
"transformers",
"gguf",
"mixture of experts",
"moe",
"8x3B",
"Llama 3.2 MOE",
"128k context",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"roma... | null | 2025-12-01T22:23:49Z | ## 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_... | [] |
xummer/gemma2-9b-nli-lora-es | xummer | 2026-03-17T03:15:45Z | 26 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:google/gemma-2-9b-it",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:google/gemma-2-9b-it",
"license:other",
"region:us"
] | text-generation | 2026-03-14T17:01:58Z | <!-- 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. -->
# es
This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the nli_es_train ... | [] |
suv11235/olmOCR-7B-grpo-v6 | suv11235 | 2025-12-10T01:13:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"generated_from_trainer",
"grpo",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:allenai/olmOCR-2-7B-1025",
"base_model:finetune:allenai/olmOCR-2-7B-1025",
"text-generation-inference",
"endpoints_compatible",
"reg... | image-text-to-text | 2025-12-09T22:29:24Z | # Model Card for grpo_training
This model is a fine-tuned version of [allenai/olmOCR-2-7B-1025](https://huggingface.co/allenai/olmOCR-2-7B-1025).
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... | [] |
dianavdavidson/wh_medium_mucs_no_langid_mucs_48419_trial | dianavdavidson | 2026-02-18T23:09:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:openai/whisper-medium",
"base_model:finetune:openai/whisper-medium",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-02-18T21:10:04Z | <!-- 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. -->
# wh_medium_mucs_no_langid_mucs_48419_trial
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/op... | [] |
cstr/moonshine-base-uk-GGUF | cstr | 2026-04-26T20:13:45Z | 0 | 0 | ggml | [
"ggml",
"gguf",
"audio",
"speech-recognition",
"transcription",
"moonshine",
"lightweight",
"automatic-speech-recognition",
"uk",
"base_model:UsefulSensors/moonshine-base-uk",
"base_model:quantized:UsefulSensors/moonshine-base-uk",
"license:other",
"region:us"
] | automatic-speech-recognition | 2026-04-26T06:21:50Z | # Moonshine Base (Ukrainian) -- GGUF
GGUF conversions and quantisations of [`UsefulSensors/moonshine-base-uk`](https://huggingface.co/UsefulSensors/moonshine-base-uk) for use with **[CrispStrobe/CrispASR](https://github.com/CrispStrobe/CrispASR)**.
## Available variants
| File | Quant | Size | Notes |
|---|---|---|-... | [] |
FrankCCCCC/ddpm_ema_cifar10 | FrankCCCCC | 2025-10-29T16:03:53Z | 2 | 1 | diffusers | [
"diffusers",
"safetensors",
"unconditional-image-generation",
"en",
"dataset:uoft-cs/cifar10",
"arxiv:2006.11239",
"license:apache-2.0",
"diffusers:DDPMPipeline",
"region:us"
] | unconditional-image-generation | 2025-08-08T15:50:14Z | # DDPM EMA CIFAR-10
## Model Description
This model is an EMA (Exponential Moving Average) version of the DDPM (Denoising Diffusion Probabilistic Models) trained on CIFAR-10 dataset. It's based on the original [DDPM](https://github.com/hojonathanho/diffusion) model but uses exponential moving averages of model parame... | [] |
OpenOneRec/OneRec-1.7B | OpenOneRec | 2026-01-05T07:06:33Z | 9,843 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"arxiv:2512.24762",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-30T15:12:32Z | <div align="center">
<h1>OpenOneRec</h1>
<p align="center">
<strong>An Open Foundation Model and Benchmark to Accelerate Generative Recommendation</strong>
</p>
<p align="center">
<a href="https://huggingface.co/OpenOneRec">
<img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%... | [] |
phospho-app/ACT-dataset_navidad_v20-s2tuq9lviv | phospho-app | 2025-11-22T15:21:15Z | 0 | 0 | phosphobot | [
"phosphobot",
"act",
"robotics",
"dataset:DavidVillanueva/dataset_navidad_v20",
"region:us"
] | robotics | 2025-11-22T14:20:52Z | ---
datasets: DavidVillanueva/dataset_navidad_v20
library_name: phosphobot
pipeline_tag: robotics
model_name: act
tags:
- phosphobot
- act
task_categories:
- robotics
---
# act model - 🧪 phosphobot training pipeline
- **Dataset**: [DavidVillanueva/dataset_navidad_v20](https://huggingface.co/datasets/DavidVillanueva/... | [] |
XpressAI/Qwen3.5-27B-RYS-GGUF | XpressAI | 2026-03-27T11:25:13Z | 466 | 0 | null | [
"gguf",
"qwen3.5",
"rys",
"layer-surgery",
"reasoning",
"mamba",
"hybrid",
"en",
"license:apache-2.0",
"region:us"
] | null | 2026-03-26T11:55:20Z | # Qwen3.5-27B — RYS Layer Surgery (GGUF)
Two modified versions of [Qwen3.5-27B-Instruct](https://huggingface.co/Qwen/Qwen3.5-27B-Instruct) produced by
**RYS layer duplication** — no training, no weight changes, just routing hidden states through a specific circuit twice.
Based on [David Ng's RYS method](https://dnhkn... | [] |
AshwinKM2005/serl-checkpoints | AshwinKM2005 | 2026-03-11T10:01:38Z | 0 | 0 | null | [
"safetensors",
"serl",
"reinforcement-learning",
"qwen2.5",
"checkpoints",
"license:apache-2.0",
"region:us"
] | reinforcement-learning | 2026-01-21T14:24:04Z | # SeRL Training Checkpoints
Compressed checkpoints from SeRL (Self-Evolving Reinforcement Learning) experiments.
Files use **ZipNN lossless compression** (~33% smaller, transparent loading).
## Quick Start
```bash
pip install zipnn huggingface_hub transformers
```
```python
# Enable ZipNN transparent loading
from z... | [] |
msiddique1436/qwen2.5-VL-7b-instruct-trl-sft-ADAS-Full | msiddique1436 | 2025-10-07T05:24:02Z | 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 | 2025-10-06T19:28:33Z | # Model Card for qwen2.5-VL-7b-instruct-trl-sft-ADAS-Full
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
question ... | [] |
Adanato/Mistral-Nemo-Instruct-2407_qwen25_qwen3_rank_diff-qwen25_qwen3_rank_diff_cluster_1 | Adanato | 2026-02-09T04:39:41Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:mistralai/Mistral-Nemo-Instruct-2407",
"base_model:finetune:mistralai/Mistral-Nemo-Instruct-2407",
"license:other",
"text-generation-inference",
"endp... | text-generation | 2026-02-09T04:35:59Z | <!-- 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. -->
# Mistral-Nemo-Instruct-2407_e1_qwen25_qwen3_rank_diff_cluster_1
This model is a fine-tuned version of [mistralai/Mistral-Nemo-Inst... | [] |
runchat/lora-533d7b31-63fd-42a0-be75-b68de7db171f-qtln4q | runchat | 2025-08-21T03:30:32Z | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"text-to-image",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-08-21T03:30:24Z | # Flux LoRA: sks
This is a LoRA (Low-Rank Adaptation) model for Flux.1-dev fine-tuned on images with the trigger word `sks`.
## Files
- `pytorch_lora_weights.safetensors`: Diffusers format (use with diffusers library)
- `pytorch_lora_weights_webui.safetensors`: Kohya format (use with AUTOMATIC1111, ComfyUI, etc.)
#... | [] |
RXY-iit/my_policy | RXY-iit | 2025-12-16T16:45:07Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:RXY-iit/act_so101_drop2cap",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-16T16:44:23Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
Muapi/neytiri-flux-sdxl | Muapi | 2025-08-19T15:19:26Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T15:19:16Z | # Neytiri (FLUX + SDXL)
**Base model**: Flux.1 D
**Trained words**: Neytiri, blue skin
## 🧠 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"
headers =... | [] |
Muapi/high-key-lighting-style-xl-f1d-pony-illu | Muapi | 2025-08-16T16:45:37Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-16T16:45:27Z | # High-key lighting Style XL + F1D + Pony + Illu
**Base model**: Flux.1 D
**Trained words**: bright light, bright shadow, High-key lighting Style
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = ... | [] |
manancode/opus-mt-zls-zls-ctranslate2-android | manancode | 2025-08-13T00:08:44Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-13T00:08:29Z | # opus-mt-zls-zls-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-zls-zls` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-zls-zls
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Convert... | [] |
Parveshiiii/Auto-Completer-0.1 | Parveshiiii | 2025-09-09T12:28:44Z | 1 | 1 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"auto-completion",
"long-context",
"smollm2",
"fine-tuned",
"en",
"base_model:HuggingFaceTB/SmolLM2-360M",
"base_model:finetune:HuggingFaceTB/SmolLM2-360M",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",... | text-generation | 2025-09-09T09:12:59Z | # 🧠 Auto-Completer-0.1
<div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/677fcdf29b9a9863eba3f29f/0go71V9BNC6wAjagdNVlp.png" width="600"/>
</div>
**Auto-Completer-0.1** is a fine-tuned version of [SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M), optimized for **l... | [] |
flymy-ai/qwen-image-edit-2509-inscene-lora | flymy-ai | 2025-09-26T16:32:46Z | 91 | 35 | diffusers | [
"diffusers",
"lora",
"qwen",
"qwen-image",
"qwen-image-edit",
"image-editing",
"inscene",
"spatial-understanding",
"scene-coherence",
"computer-vision",
"InScene",
"image-to-image",
"en",
"base_model:Qwen/Qwen-Image-Edit-2509",
"base_model:adapter:Qwen/Qwen-Image-Edit-2509",
"license:a... | image-to-image | 2025-09-25T10:51:01Z | # Qwen Image Edit Inscene LoRA
An open-source LoRA (Low-Rank Adaptation) model for Qwen-Image-Edit that specializes in in-scene image editing by [FlyMy.AI](https://flymy.ai).
## 🌟 About FlyMy.AI
Agentic Infra for GenAI. FlyMy.AI is a B2B infrastructure for building and running GenAI Media agents.
**🔗 Useful Links... | [] |
OpenMed/OpenMed-PII-Dutch-SuperClinical-Small-44M-v1 | OpenMed | 2026-03-09T13:56:16Z | 31 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"token-classification",
"ner",
"pii",
"pii-detection",
"de-identification",
"privacy",
"healthcare",
"medical",
"clinical",
"phi",
"dutch",
"pytorch",
"openmed",
"nl",
"base_model:microsoft/deberta-v3-small",
"base_model:finetune:micro... | token-classification | 2026-03-08T22:59:09Z | # OpenMed-PII-Dutch-SuperClinical-Small-44M-v1
**Dutch PII Detection Model** | 44M Parameters | Open Source
[]() []() []()
#... | [] |
kkh27/healthcareLLM_v4_Tri-7B | kkh27 | 2025-08-18T08:17:59Z | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | 2025-08-18T07:35:31Z | ## 🛠️ Model Details
- **Base Model**: `trillionslabs/Tri-7B`
- **Model Size**: 7.53B
- **Fine-tuned by**: [kkh27](https://huggingface.co/kkh27)
- **Training Framework**: Hugging Face Transformers + PEFT (LoRA)
- **Precision**: bfloat16 (bf16)
- **Language**: Korean
---
## 🧪 Training Configuration
### ... | [] |
y-tani/dpo-qwen-cot-v4-merged | y-tani | 2026-02-18T17:14:00Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"dpo",
"qwen",
"alignment",
"conversational",
"en",
"dataset:u-10bei/dpo-dataset-qwen-cot",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:quantized:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-generation-infere... | text-generation | 2026-02-18T17:13:02Z | # y-tani/dpo-qwen-cot-v4-merged
This model is a fine-tuned version of **Qwen/Qwen3-4B-Instruct-2507** using a two-stage pipeline:
1. **SFT (Supervised Fine-Tuning)**: LoRA adapter from [y-tani/lora_structeval_t_qwen3_4b_v4](https://huggingface.co/y-tani/lora_structeval_t_qwen3_4b_v4)
2. **DPO (Direct Preference Optim... | [
{
"start": 137,
"end": 140,
"text": "SFT",
"label": "training method",
"score": 0.7226725220680237
},
{
"start": 292,
"end": 295,
"text": "DPO",
"label": "training method",
"score": 0.8649896383285522
},
{
"start": 535,
"end": 538,
"text": "SFT",
"labe... |
a3ilab-llm-uncertainty/gptoss_20b_all_zhtw_lr5e-7_ep5_16_64_128_turn_clean_v1_data_500 | a3ilab-llm-uncertainty | 2026-03-26T13:54:02Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:openai/gpt-oss-20b",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:openai/gpt-oss-20b",
"license:other",
"region:us"
] | text-generation | 2026-03-25T07:44:09Z | <!-- 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. -->
# gptoss_20b_all_zhtw_lr5e-7_ep5_16_64_128_turn_clean_v1_data_500
This model is a fine-tuned version of [openai/gpt-oss-20b](https:... | [] |
mt628754/test054 | mt628754 | 2026-02-28T04:44:20Z | 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 | 2026-02-28T04:42:40Z | # qwen3-4b-agent-trajectory-lora-1
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 improve **multi-... | [
{
"start": 65,
"end": 69,
"text": "LoRA",
"label": "training method",
"score": 0.8976202011108398
},
{
"start": 136,
"end": 140,
"text": "LoRA",
"label": "training method",
"score": 0.9230801463127136
},
{
"start": 182,
"end": 186,
"text": "LoRA",
"lab... |
DarwinDanish/exoplanet-classifier-stacking | DarwinDanish | 2025-11-23T13:28:19Z | 0 | 0 | sklearn | [
"sklearn",
"exoplanets",
"astronomy",
"tabular-classification",
"stacking",
"lightgbm",
"xgboost",
"catboost",
"physics",
"license:mit",
"region:us"
] | tabular-classification | 2025-11-23T13:08:58Z | # Model Card: Exoplanet Candidate Classifier (Stacking Ensemble)
## Model Details
### Model Description
This is a robust machine learning pipeline designed to classify **Kepler Objects of Interest (KOIs)**. It determines whether a detected signal represents a real exoplanet or a false positive.
The model utilizes a... | [] |
AnonymousCS/populism_classifier_033 | AnonymousCS | 2025-08-25T21:33:52Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:google-bert/bert-base-multilingual-uncased",
"base_model:finetune:google-bert/bert-base-multilingual-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatib... | text-classification | 2025-08-25T21:32:45Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# populism_classifier_033
This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co... | [] |
nikolayons04nn/wide-lapel_LoRA | nikolayons04nn | 2026-03-25T11:03:55Z | 0 | 0 | diffusers | [
"diffusers",
"tensorboard",
"text-to-image",
"diffusers-training",
"lora",
"template:sd-lora",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"re... | text-to-image | 2026-03-24T13:06:00Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - nikolayons04nn/wide-lapel_LoRA
<Gallery />
## Model description
These are nikolayons04nn/wide-l... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7710244059562683
},
{
"start": 330,
"end": 334,
"text": "LoRA",
"label": "training method",
"score": 0.8026093244552612
},
{
"start": 477,
"end": 481,
"text": "LoRA",
"l... |
ayushadarsh7/gemma_3_only_projector | ayushadarsh7 | 2025-11-10T07:04:06Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3",
"image-text-to-text",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:google/gemma-3-4b-it",
"base_model:finetune:google/gemma-3-4b-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-11-10T03:24:36Z | # Model Card for gemma_3_only_projector
This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-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, bu... | [] |
mradermacher/Qwen3-0.6B-Dakota-Grammar-RL-GGUF | mradermacher | 2025-11-10T15:54:16Z | 20 | 0 | transformers | [
"transformers",
"gguf",
"reinforcement-learning",
"rl",
"dakota-language",
"grammar",
"composition-rewards",
"non-coding",
"prime-intellect",
"verifiers",
"en",
"dak",
"base_model:HarleyCooper/Qwen3-0.6B-Dakota-Grammar-RL",
"base_model:quantized:HarleyCooper/Qwen3-0.6B-Dakota-Grammar-RL",
... | reinforcement-learning | 2025-11-10T15:29:37Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
wuc1/bi_so101_flatten-and-fold-the-rag-then-place-0416-0417-merge-0418-model | wuc1 | 2026-04-18T05:50:12Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:wuc1/bi_so101_flatten-and-fold-the-rag-then-place-0416-0417-merge",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-17T19:44:00Z | # 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... | [] |
alonsoko/MiniMax-M2.5-heretic-ara-AWQ | alonsoko | 2026-04-07T15:41:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"minimax_m2",
"text-generation",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"minimax",
"minimax m2.5",
"conversational",
"custom_code",
"base_model:RadicalNotionAI/MiniMax-M2.5-bf16-heretic",
"base_model:quantized:RadicalNotionAI/MiniMax-M... | text-generation | 2026-04-07T15:33:45Z | # This is a decensored version of [PrimeIntellect/MiniMax-M2.5-bf16](https://huggingface.co/PrimeIntellect/MiniMax-M2.5-bf16), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0+custom with the [Arbitrary-Rank Ablation (ARA)](https://github.com/p-e-w/heretic/pull/211) method
## Abliteration parameters
| Pa... | [] |
mradermacher/gpt-oss-20b-offload-GGUF | mradermacher | 2025-09-11T12:00:07Z | 59 | 0 | transformers | [
"transformers",
"gguf",
"gpt-oss",
"openai",
"mxfp4",
"mixture-of-experts",
"causal-lm",
"text-generation",
"cpu-gpu-offload",
"colab",
"en",
"dataset:openai/gpt-oss-training-data",
"base_model:myselfsaurabh/gpt-oss-20b-offload",
"base_model:quantized:myselfsaurabh/gpt-oss-20b-offload",
... | text-generation | 2025-09-11T01:28:31Z | ## 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... | [] |
FiveC/Long_attention_Longformer | FiveC | 2026-03-05T09:55:54Z | 0 | 0 | null | [
"pytorch",
"tensorboard",
"generated_from_trainer",
"base_model:allenai/led-base-16384",
"base_model:finetune:allenai/led-base-16384",
"license:apache-2.0",
"region:us"
] | null | 2026-03-05T03:06:32Z | <!-- 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. -->
# Long_attention_Longformer
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-... | [] |
itextresearch/itext-PP-OCRv5_server_rec_infer | itextresearch | 2026-03-23T10:09:24Z | 0 | 0 | null | [
"onnx",
"license:apache-2.0",
"region:us"
] | null | 2026-03-09T10:35:44Z | # <h1>itext-PP-OCRv5_server_rec_infer</h1>
These are machine learning models designed to detect and recognize text within images. They analyze visual input, identify regions containing text, and convert that text into a machine-readable format. We integrate these models into our iText PdfOCR ONNX engine to enable effic... | [] |
QuantFactory/Qwen2.5-Coder-7B-GGUF | QuantFactory | 2024-09-19T06:02:10Z | 1,523 | 7 | transformers | [
"transformers",
"gguf",
"code",
"qwen",
"qwen-coder",
"codeqwen",
"text-generation",
"en",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-7B",
"base_model:quantized:Qwen/Qwen2.5-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2024-09-19T05:21:50Z | ---
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-7B/blob/main/LICENSE
language:
- en
base_model:
- Qwen/Qwen2.5-7B
pipeline_tag: text-generation
library_name: transformers
tags:
- code
- qwen
- qwen-coder
- codeqwen
---
[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz... | [] |
mkit/Yuan3.0-Flash-GGUF | mkit | 2026-03-23T16:30:01Z | 78 | 0 | null | [
"gguf",
"yuan",
"yuanvl",
"multimodal",
"vision-language",
"moe",
"quantized",
"arxiv:2601.01718",
"base_model:YuanLabAI/Yuan3.0-Flash",
"base_model:quantized:YuanLabAI/Yuan3.0-Flash",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-22T14:33:34Z | # Yuan3.0-Flash-GGUF
> ⚠️ **Bleeding Edge**: This GGUF requires a custom llama.cpp build with Yuan3.0 support. Not yet in mainstream llama.cpp.
>
> See [Links](#links) below for the custom branch and Docker images.
GGUF quantized versions of [YuanLabAI/Yuan3.0-Flash](https://huggingface.co/YuanLabAI/Yuan3.0-Flash), ... | [] |
unsloth/Qwen3-VL-32B-Thinking-1M-GGUF | unsloth | 2025-11-02T01:29:16Z | 4,410 | 4 | transformers | [
"transformers",
"gguf",
"unsloth",
"image-text-to-text",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen3-VL-32B-Thinking",
"base_model:quantized:Qwen/Qwen3-VL-32B-Thinking",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"i... | image-text-to-text | 2025-11-01T23:17:05Z | > [!NOTE]
> Includes Unsloth **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
>
<div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
... | [] |
TMLR-Group-HF/Entropy-Qwen3-8B-Base-MATH | TMLR-Group-HF | 2025-08-05T07:10:31Z | 3 | 1 | null | [
"safetensors",
"qwen3",
"arxiv:2508.00410",
"license:mit",
"region:us"
] | null | 2025-08-05T03:49:11Z | ## TMLR-Group-HF/Entropy-Qwen3-8B-Base
This is the Qwen3-8B-Base model trained by Entropy Minimization method using MATH training set.
If you are interested in Co-Reward, you can find more details on our Github Repo [https://github.com/tmlr-group/Co-Reward].
## Citation
```
@article{zhang2025coreward,
title={C... | [
{
"start": 83,
"end": 110,
"text": "Entropy Minimization method",
"label": "training method",
"score": 0.8705896139144897
}
] |
da1ch812/advanced-comp-model-20260301095013 | da1ch812 | 2026-03-01T02:26:32Z | 14 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v2",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v3",
"dataset:u-10bei/sft_alfworld_trajectory_datase... | text-generation | 2026-03-01T02:25:05Z | # ＜qwen3-4b-agent-trajectory-lora＞
This repository provides a merged model that includes both the base model
**unsloth/Qwen3-4B-Instruct-2507** and the LoRA adapter. No separate LoRA loading is required.
## Training Objective
This adapter is trained to improve **multi-turn agent task performance**
on ALFWorld (house... | [
{
"start": 153,
"end": 157,
"text": "LoRA",
"label": "training method",
"score": 0.8606616854667664
},
{
"start": 179,
"end": 183,
"text": "LoRA",
"label": "training method",
"score": 0.8387871384620667
},
{
"start": 631,
"end": 635,
"text": "LoRA",
"l... |
ferrazzipietro/ULS-MultiClinNERes-Qwen2.5-7B-Instruct-disease | ferrazzipietro | 2026-03-13T23:46:51Z | 106 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"lora",
"transformers",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-03-13T23:27:19Z | <!-- 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. -->
# ULS-MultiClinNERes-Qwen2.5-7B-Instruct-disease
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingfa... | [] |
nightmedia/LFM2-350M-Math-q5-hi-mlx | nightmedia | 2025-10-01T12:27:52Z | 5 | 0 | mlx | [
"mlx",
"safetensors",
"lfm2",
"liquid",
"edge",
"text-generation",
"conversational",
"en",
"base_model:LiquidAI/LFM2-350M-Math",
"base_model:quantized:LiquidAI/LFM2-350M-Math",
"license:other",
"5-bit",
"region:us"
] | text-generation | 2025-09-30T16:56:49Z | # LFM2-350M-Math-q5-hi-mlx
Comparative Analysis: LFM2-350M-Math Quantized Variants
```bash
Model arc_challenge arc_easy boolq hellaswag openbookqa piqa winogrande
LFM2-350M-Math-mxfp4 0.262 0.372 0.382 0.301 0.304 0.530 0.489
LFM2-350M-Math-q5-hi 0.265 0.367 0.379 0.307 0.312 0.532 0.490
LFM2-350M-Math-q5 ... | [] |
AksaraLLM/Kiel-Pro-0.5B-v3-GGUF | AksaraLLM | 2026-05-02T17:09:27Z | 0 | 0 | gguf | [
"gguf",
"llama.cpp",
"ollama",
"indonesian",
"aksarallm",
"qwen2",
"text-generation",
"id",
"base_model:AksaraLLM/Kiel-Pro-0.5B-v3",
"base_model:quantized:AksaraLLM/Kiel-Pro-0.5B-v3",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-05-02T12:23:04Z | # Kiel-Pro-0.5B-v3-GGUF
GGUF quantizations of [`AksaraLLM/Kiel-Pro-0.5B-v3`](https://huggingface.co/AksaraLLM/Kiel-Pro-0.5B-v3) for inference with [llama.cpp](https://github.com/ggml-org/llama.cpp), [Ollama](https://ollama.ai), [LM Studio](https://lmstudio.ai), and other GGUF runtimes.
## Files
| File | Quant | Size... | [] |
JThomas-CoE/CoE-WEB2-40b-A3b-GGUF | JThomas-CoE | 2026-03-10T23:35:46Z | 30 | 0 | null | [
"gguf",
"moe",
"qwen",
"code",
"en",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-07T22:46:21Z | # Separability of Intelligence in Mixture-of-Experts: Slicing Qwen3-Coder into Independent Domain Specialists
**Author:** J. Thomas
**Context:** College of Experts Architecture Validation — Proof of Principle
**Date:** March 2026
---
## Abstract
Recent experiments with the `Qwen3-Coder-Next-80B-A3B` Mixture-of-Expe... | [
{
"start": 883,
"end": 892,
"text": "HumanEval",
"label": "training method",
"score": 0.8183693885803223
},
{
"start": 977,
"end": 986,
"text": "HumanEval",
"label": "training method",
"score": 0.8208039402961731
},
{
"start": 1134,
"end": 1143,
"text": "H... |
mradermacher/Gaperon-1125-8B-GGUF | mradermacher | 2025-11-10T17:02:05Z | 117 | 0 | transformers | [
"transformers",
"gguf",
"gaperon",
"fr",
"en",
"dataset:togethercomputer/RedPajama-Data-V2",
"dataset:HuggingFaceFW/fineweb-edu",
"dataset:LLM360/TxT360",
"dataset:bigcode/the-stack-v2-train-smol-ids",
"base_model:almanach/Gaperon-1125-8B",
"base_model:quantized:almanach/Gaperon-1125-8B",
"lic... | null | 2025-10-29T12:24:45Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
zzq1zh/xvla-mink-merged-3cams-v6-12000steps-v | zzq1zh | 2026-04-07T02:40:48Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"xvla",
"robotics",
"dataset:local/dataset_large_merged_v6",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-07T02:40:14Z | # Model Card for xvla
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.c... | [] |
Sambhavnoobcoder/gpt2-test-quantization-Quanto-int8 | Sambhavnoobcoder | 2026-01-10T20:37:03Z | 1 | 0 | null | [
"pytorch",
"safetensors",
"gpt2",
"quantized",
"quanto",
"int8",
"automatic-quantization",
"base_model:Sambhavnoobcoder/gpt2-test-quantization",
"base_model:finetune:Sambhavnoobcoder/gpt2-test-quantization",
"license:apache-2.0",
"region:us"
] | null | 2026-01-10T19:36:24Z | # gpt2-test-quantization - Quanto int8
This is an **automatically quantized** version of [Sambhavnoobcoder/gpt2-test-quantization](https://huggingface.co/Sambhavnoobcoder/gpt2-test-quantization) using [Quanto](https://github.com/huggingface/optimum-quanto) int8 quantization.
## ⚡ Quick Start
```python
from transform... | [] |
arcee-ai/Trinity-Mini-Base | arcee-ai | 2025-12-11T21:45:11Z | 1,560 | 19 | transformers | [
"transformers",
"safetensors",
"afmoe",
"text-generation",
"conversational",
"custom_code",
"en",
"es",
"fr",
"de",
"it",
"pt",
"ru",
"ar",
"hi",
"ko",
"zh",
"base_model:arcee-ai/Trinity-Mini-Base-Pre-Anneal",
"base_model:finetune:arcee-ai/Trinity-Mini-Base-Pre-Anneal",
"licens... | text-generation | 2025-12-01T18:25:42Z | <div align="center">
<picture>
<img
src="https://cdn-uploads.huggingface.co/production/uploads/6435718aaaef013d1aec3b8b/i-v1KyAMOW_mgVGeic9WJ.png"
alt="Arcee Trinity Mini"
style="max-width: 100%; height: auto;"
>
</picture>
</div>
# Trinity Mini Base
Trinity Mini is an Arcee AI 26B MoE m... | [] |
mlx-community/Josiefied-Qwen3-4B-Instruct-2507-abliterated-v1-6bit | mlx-community | 2025-10-29T10:58:52Z | 12 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3",
"chat",
"text-generation",
"conversational",
"base_model:Goekdeniz-Guelmez/Josiefied-Qwen3-4B-Instruct-2507-abliterated-v1",
"base_model:quantized:Goekdeniz-Guelmez/Josiefied-Qwen3-4B-Instruct-2507-abliterated-v1",
"6-bit",
"region:us"
] | text-generation | 2025-10-29T10:49:29Z | # mlx-community/Josiefied-Qwen3-4B-Instruct-2507-abliterated-v1-6bit
This model [mlx-community/Josiefied-Qwen3-4B-Instruct-2507-abliterated-v1-6bit](https://huggingface.co/mlx-community/Josiefied-Qwen3-4B-Instruct-2507-abliterated-v1-6bit) was
converted to MLX format from [Goekdeniz-Guelmez/Josiefied-Qwen3-4B-Instruct... | [] |
JOhyeongi/vet-kmbert-cross-encoder | JOhyeongi | 2025-12-08T10:41:45Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"cross-encoder",
"veterinary",
"medical",
"korean",
"text-classification",
"ko",
"dataset:custom",
"base_model:madatnlp/km-bert",
"base_model:finetune:madatnlp/km-bert",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2025-12-08T10:41:38Z | # 🏥 Vet KM-BERT Cross-Encoder
수의학 도메인에 특화된 한국어 Cross-Encoder 모델입니다. RAG 시스템의 Reranking 단계에서 사용됩니다.
## 모델 정보
- **Base Model**: [madatnlp/km-bert](https://huggingface.co/madatnlp/km-bert)
- **Task**: Binary Classification (질문-문서 연관성 판단)
- **Language**: Korean (한국어)
- **Domain**: Veterinary Medicine (수의학)
... | [] |
Moto2064/my_first_pick_and_place_policy | Moto2064 | 2025-10-19T02:11:56Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:Moto2064/record-test-v3",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-18T19:43:22Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
viamr-project/qwen3-1.7b-amr-augmented-20260214-0713 | viamr-project | 2026-02-14T03:32:47Z | 2 | 0 | null | [
"safetensors",
"qwen3",
"region:us"
] | null | 2026-02-14T03:04:02Z | # qwen3-1.7b-amr-augmented-20260214-0713
## Model Information
- **Timestamp**: 20260214_112916
## Benchmark Results
- **Benchmark File**: viamr-project_qwen3-1.7b-amr-augmented-20260214-0713.jsonl
- **Score**:
- **F1**: 81.68
- **Precision**: 82.56
- **Recall**: 80.82
## Usage
```python
from transformers import... | [] |
MariaFGI/ModernBERT-base-finetuned-modernbert | MariaFGI | 2025-10-26T14:22:26Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"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 | 2025-09-23T12:59:17Z | <!-- 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. -->
# ModernBERT-base-finetuned-modernbert
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/a... | [] |
OpenGVLab/InternVL3_5-38B-HF | OpenGVLab | 2025-09-08T10:02:58Z | 1,707 | 6 | transformers | [
"transformers",
"safetensors",
"internvl",
"image-text-to-text",
"custom_code",
"conversational",
"multilingual",
"dataset:OpenGVLab/MMPR-v1.2",
"dataset:OpenGVLab/MMPR-Tiny",
"arxiv:2312.14238",
"arxiv:2404.16821",
"arxiv:2412.05271",
"arxiv:2411.10442",
"arxiv:2504.10479",
"arxiv:2508.... | image-text-to-text | 2025-08-29T13:16:54Z | # InternVL3_5-38B
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggingface.co/pa... | [] |
mradermacher/QwensanLoRA-3B-Merge-i1-GGUF | mradermacher | 2025-12-27T02:00:15Z | 110 | 1 | transformers | [
"transformers",
"gguf",
"mental-health",
"counseling",
"indonesia",
"qwen",
"lora",
"qlora",
"id",
"dataset:Amod/mental_health_counseling_conversations",
"dataset:ShenLab/MentalChat16K",
"base_model:XzyanQi/QwensanLoRA-3B-Merge",
"base_model:adapter:XzyanQi/QwensanLoRA-3B-Merge",
"endpoint... | null | 2025-12-26T23:58:53Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
J-Barrert/BridgeLang-Core | J-Barrert | 2025-12-15T20:43:08Z | 0 | 0 | null | [
"safetensors",
"license:apache-2.0",
"region:us"
] | null | 2025-12-15T20:22:41Z | ---
license: apache-2.0
---
**Code Repository:** [GitHub - BridgeLang](https://github.com/jjwbarrett-jpg/BridgeLang)
# BridgeLang (v0.1 Alpha)
# BridgeLang (v0.1 Alpha)
**A Hybrid NLU Interceptor for Deterministic Agent Control**
## 🚀 Overview
BridgeLang is a middleware architecture designed to solve the "Stochas... | [] |
SaeedLab/MolDeBERTa-small-10M-contrastive_mlc | SaeedLab | 2026-04-28T16:46:16Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"feature-extraction",
"chemistry",
"bioinformatics",
"drug-discovery",
"dataset:SaeedLab/MolDeBERTa",
"license:cc-by-nc-nd-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2026-01-19T22:51:58Z | # MolDeBERTa-small-10M-contrastive_mlc
This model corresponds to the MolDeBERTa small architecture pretrained on the 10M dataset using the contrastive MLC pretraining objective.
\[[Github Repo](https://github.com/pcdslab/MolDeBERTa)\] | \[[Dataset on HuggingFace](https://huggingface.co/datasets/SaeedLab/MolDeBERTa)\]... | [] |
ahmedHamdi/story-similarity-mpnet-plots-pt-en-NE-Masked | ahmedHamdi | 2026-01-23T07:41:51Z | 12 | 0 | sentence-transformers | [
"sentence-transformers",
"tensorboard",
"safetensors",
"mpnet",
"sentence-similarity",
"feature-extraction",
"autotrain",
"base_model:sentence-transformers/all-mpnet-base-v2",
"base_model:finetune:sentence-transformers/all-mpnet-base-v2",
"text-embeddings-inference",
"endpoints_compatible",
"r... | sentence-similarity | 2026-01-22T12:27:03Z | ---
library_name: sentence-transformers
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- autotrain
base_model: sentence-transformers/all-mpnet-base-v2
widget:
- source_sentence: 'search_query: i love autotrain'
sentences:
- 'search_query: huggingface auto train'
- 'search_query: hugging ... | [] |
zonglin11/stir_wine_new | zonglin11 | 2025-10-15T12:59:51Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:Keith-Luo/stir_wine_new",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-15T12:59:02Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
KKHYA/llavaqwen3-1.7b-finetune-moe-4e-2k_20260427_233320 | KKHYA | 2026-04-28T03:46:08Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"moe_llava_qwen3",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:KKHYA/llavaqwen3-1.7b-finetune",
"base_model:finetune:KKHYA/llavaqwen3-1.7b-finetune",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-27T23:37:57Z | <!-- 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. -->
# llavaqwen3-1.7b-finetune-moe-4e-2k_20260427_233320
This model is a fine-tuned version of [KKHYA/llavaqwen3-1.7b-finetune](https:/... | [] |
fn-aka-mur/adv_sft_0005_cont0002_lr2e6_1ep | fn-aka-mur | 2026-02-17T05:16:05Z | 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:fn-aka-mur/adv_sft_0002",
"base_model:adapter:fn-aka-mur/adv_sft_0002",
"license:apache-2.0",
... | text-generation | 2026-02-17T05:14:23Z | # Qwen3-4B-Instruct-2507-LoRA-AgentBench
This repository provides a **LoRA adapter** fine-tuned from
**fujiki/adv_sft_0002** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **multi-tu... | [
{
"start": 71,
"end": 75,
"text": "LoRA",
"label": "training method",
"score": 0.8264365792274475
},
{
"start": 134,
"end": 138,
"text": "LoRA",
"label": "training method",
"score": 0.8457006812095642
},
{
"start": 180,
"end": 184,
"text": "LoRA",
"lab... |
msochan/stable-diffusion-xl-base-1.0 | msochan | 2026-03-14T17:55:18Z | 289 | 0 | diffusers | [
"diffusers",
"onnx",
"safetensors",
"text-to-image",
"stable-diffusion",
"arxiv:2307.01952",
"arxiv:2211.01324",
"arxiv:2108.01073",
"arxiv:2112.10752",
"license:openrail++",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | 2026-03-14T17:55:17Z | # SD-XL 1.0-base Model Card
## Model
[SDXL](https://arxiv.org/abs/2307.01952) consists of an [ensemble of experts](https://arxiv.org/abs/2211.01324) pipeline for latent diffusion:
In a first step, the base model is used to generate (noisy) latents,
which are then further ... | [] |
Shoriful025/customer_feedback_sentiment_bert | Shoriful025 | 2026-01-04T06:43:16Z | 6 | 0 | null | [
"bert",
"nlp",
"sentiment-analysis",
"classification",
"en",
"license:apache-2.0",
"region:us"
] | null | 2026-01-04T06:42:50Z | # customer_feedback_sentiment_bert
## Overview
This model is a fine-tuned BERT (Bidirectional Encoder Representations from Transformers) model designed to categorize customer feedback into three distinct sentiment classes: Negative, Neutral, and Positive. It is optimized for short-to-medium length text such as product... | [] |
aoxo/gpt-oss-20b-uncensored | aoxo | 2026-03-10T12:58:32Z | 22,641 | 25 | transformers | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"vllm",
"llm",
"open-source",
"conversational",
"en",
"arxiv:2508.10925",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-22T13:14:47Z | <p align="center">
<img alt="gpt-oss-20b-abliterated" src="https://raw.githubusercontent.com/aloshdenny/openai/master/gpt-oss-20b-uncensored.png">
</p>
#### Model Overview
**Model Name:** gpt-oss-20b-uncensored
**Model Type:** Large Language Model (Text Generation)
**Architecture:** Decoder-Only Transformer (Mix... | [
{
"start": 827,
"end": 839,
"text": "abliteration",
"label": "training method",
"score": 0.7115034461021423
}
] |
ORI-Muchim/openaudio-s1-mini-int8 | ORI-Muchim | 2026-01-20T19:42:54Z | 44 | 6 | null | [
"dual_ar",
"text-to-speech",
"zh",
"en",
"de",
"ja",
"fr",
"es",
"ko",
"ar",
"nl",
"ru",
"it",
"pl",
"pt",
"base_model:fishaudio/openaudio-s1-mini",
"base_model:finetune:fishaudio/openaudio-s1-mini",
"license:cc-by-nc-sa-4.0",
"region:us"
] | text-to-speech | 2026-01-20T19:39:16Z | # OpenAudio S1-mini INT8 Quantized
**INT8 weight-only quantized version** of [fishaudio/openaudio-s1-mini](https://huggingface.co/fishaudio/openaudio-s1-mini) for efficient GPU inference.
## Model Size Comparison
| Model | Original | INT8 | Reduction |
|-------|----------|------|-----------|
| LLaMA (model.p... | [] |
pedrodev2026/microcoder-1.5b | pedrodev2026 | 2026-03-27T21:35:11Z | 24 | 2 | null | [
"safetensors",
"qwen2",
"coder",
"code",
"microcoder",
"text-generation",
"conversational",
"dataset:pedrodev2026/microcoder-dataset-1024-tokens",
"base_model:unsloth/Qwen2.5-Coder-1.5B-Instruct",
"base_model:finetune:unsloth/Qwen2.5-Coder-1.5B-Instruct",
"license:bsd-3-clause",
"region:us"
] | text-generation | 2026-03-27T01:26:41Z | # Microcoder 1.5B
**Microcoder 1.5B** is a code-focused language model fine-tuned from [Qwen 2.5 Coder 1.5B Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) using LoRA (Low-Rank Adaptation) on curated code datasets. It is designed for code generation, completion, and instruction-following tasks in a ... | [
{
"start": 182,
"end": 186,
"text": "LoRA",
"label": "training method",
"score": 0.8151951432228088
},
{
"start": 595,
"end": 599,
"text": "LoRA",
"label": "training method",
"score": 0.8211129307746887
}
] |
clokai/clokAI | clokai | 2026-03-21T21:21:40Z | 0 | 0 | PyTorch | [
"PyTorch",
"SNN",
"KAN",
"logic-synthesis",
"deterministic-reasoning",
"custom-architecture",
"text-generation",
"en",
"dataset:custom-entropy-corpus",
"license:mit",
"region:us"
] | text-generation | 2026-02-23T03:46:43Z | <div align="center">
```text
██████╗██╗ ██████╗ ██╗ ██╗ █████╗ ██╗
██╔════╝██║ ██╔═══██╗██║ ██╔╝██╔══██╗██║
██║ ██║ ██║ ██║█████╔╝ ███████║██║
██║ ██║ ██║ ██║██╔═██╗ ██╔══██║██║
╚██████╗███████╗╚██████╔╝██║ ██╗██║ ██║██║
╚═════╝╚══════╝ ╚═════╝ ╚═╝ ╚═╝╚═╝ ╚═╝╚═╝
///... | [] |
RemkoPr/b-n150-INSTR0-250k | RemkoPr | 2026-02-28T04:43:38Z | 30 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:RemkoPr/b-n150-PREPR-INSTR0",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-28T04:43:13Z | # 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 ... | [] |
elshadrahimov/miLLi-1.0 | elshadrahimov | 2025-12-31T08:54:24Z | 0 | 0 | null | [
"tokenizer",
"azerbaijani",
"nlp",
"morphology",
"hybrid",
"bpe",
"phonological-restoration",
"az",
"dataset:uonlp/CulturaX",
"dataset:tatoeba",
"license:apache-2.0",
"region:us"
] | null | 2025-12-27T15:04:08Z | # miLLi: Model Integrating Local Linguistic Insights for Morphologically Robust Tokenization
**miLLi 1.0** is a hybrid tokenizer specifically engineered for the **Azerbaijani language**, addressing the limitations of standard statistical models (e.g., BPE, WordPiece) in processing agglutinative morphologies. By integr... | [] |
pilipolio/chess-puzzle-sft-qwen3-4b | pilipolio | 2025-12-06T03:15:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"endpoints_compatible",
"region:us"
] | null | 2025-12-05T11:08:12Z | # Model Card for chess-puzzle-sft-qwen3-4b
This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a... | [] |
Pranilllllll/segformer-satellite-segementation | Pranilllllll | 2026-03-16T03:27:30Z | 60 | 0 | transformers | [
"transformers",
"safetensors",
"segformer",
"semantic-segmentation",
"satellite-imagery",
"remote-sensing",
"land-use",
"geospatial",
"nepal",
"kathmandu",
"image-segmentation",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | image-segmentation | 2025-12-22T01:57:24Z | # Model Card — SegFormer-B0 Kathmandu Valley Satellite Segmentation
## Model Description
This model is a fine-tuned **SegFormer-B0** for semantic segmentation of satellite imagery over **Kathmandu Valley, Nepal**. It classifies each pixel into one of 7 land-use categories: Background, Residential Area, Road, River, F... | [] |
ZafarLocAI/civ_mil_cls_mar20_kaggle_cntxt_ckpt_29_mar | ZafarLocAI | 2026-03-29T15:04:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"convnextv2",
"image-classification",
"generated_from_trainer",
"base_model:facebook/convnextv2-large-22k-224",
"base_model:finetune:facebook/convnextv2-large-22k-224",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2026-03-29T13:13:01Z | <!-- 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. -->
# civ_mil_cls_mar20_kaggle_cntxt_ckpt_29_mar
This model is a fine-tuned version of [facebook/convnextv2-large-22k-224](https://hugg... | [] |
toolevalxm/MedAssist-Pro-TestRepo | toolevalxm | 2026-03-06T02:44:46Z | 34 | 0 | transformers | [
"transformers",
"pytorch",
"llama",
"text-generation",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-05T00:23:00Z | # MedAssist-Pro
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<img src="figures/fig1.png" width="60%" alt="MedAssist-Pro" />
</div>
<hr>
<div align="center" style="line-height: 1;">
<a href="LICENSE" style="mar... | [] |
Abiray/MiniMax-M2.7-Q5_K_M-GGUF | Abiray | 2026-04-12T08:27:55Z | 0 | 0 | null | [
"gguf",
"quantized",
"llama-cpp",
"text-generation",
"base_model:MiniMaxAI/MiniMax-M2.7",
"base_model:quantized:MiniMaxAI/MiniMax-M2.7",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-04-12T08:07:13Z | <div align="center">
<svg width="60%" height="auto" viewBox="0 0 144 48" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M26.6782 7.96523C26.6782 7.02436 25.913 6.26087 24.9739 6.26087C24.0348 6.26087 23.2695 7.0261 23.2695 7.96523V36.2139C23.2695 38.4 21.4904 40.1791 19.3043 40.1791C17.1183 40.1791 15.3391 3... | [] |
alankessler/Mistral-Small-3.2-24B-Instruct-2506-MLX-mxfp8 | alankessler | 2026-03-11T06:05:50Z | 219 | 0 | mlx | [
"mlx",
"safetensors",
"mistral3",
"quantized",
"mistral",
"base_model:mistralai/Mistral-Small-3.2-24B-Instruct-2506",
"base_model:quantized:mistralai/Mistral-Small-3.2-24B-Instruct-2506",
"license:apache-2.0",
"8-bit",
"region:us"
] | null | 2026-03-11T05:59:53Z | # Mistral-Small-3.2-24B-Instruct-2506-MLX-mxfp8
MLX quantized version of [Mistral Small 3.2 24B Instruct 2506](https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506).
## Quantization
- **Method**: MXFP8 (Microscaling FP8)
- **Bits per weight**: 8 (FP)
- **Details**: 8-bit floating-point quantization u... | [] |
noctrex/Huihui-Qwen3.5-35B-A3B-abliterated-MXFP4_MOE-GGUF | noctrex | 2026-03-03T10:01:27Z | 11,149 | 8 | null | [
"gguf",
"image-text-to-text",
"base_model:huihui-ai/Huihui-Qwen3.5-35B-A3B-abliterated",
"base_model:quantized:huihui-ai/Huihui-Qwen3.5-35B-A3B-abliterated",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2026-02-27T13:42:16Z | These are quantizations of the model [Huihui-Qwen3.5-35B-A3B-abliterated](https://huggingface.co/huihui-ai/Huihui-Qwen3.5-35B-A3B-abliterated)
- Download the latest [llama.cpp](https://github.com/ggml-org/llama.cpp) to use these quantizations.
- For the `mmproj` file, the F32 version is recommended for best results.... | [] |
davidfertube/compliance-policy-checker | davidfertube | 2026-02-07T19:33:51Z | 0 | 0 | transformers | [
"transformers",
"nerc-cip",
"compliance",
"regulatory",
"power-grid",
"cybersecurity",
"text-classification",
"fine-tuned",
"lora",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-01-25T09:49:06Z | # NERC CIP Validator
> **Fine-Tuned LLM for Automated NERC CIP Compliance Assessment**
[](https://huggingface.co/spaces/davidfertube/policy-guard)
[](https://davidfernandez.dev)
##... | [] |
AfriScience-MT/gemma_2_9b_it-lora-r64-eng-lug | AfriScience-MT | 2026-04-12T03:42:57Z | 0 | 0 | peft | [
"peft",
"safetensors",
"translation",
"african-languages",
"scientific-translation",
"afriscience-mt",
"lora",
"gemma",
"en",
"lg",
"base_model:google/gemma-2-9b-it",
"base_model:adapter:google/gemma-2-9b-it",
"license:apache-2.0",
"region:us"
] | translation | 2026-04-12T03:42:36Z | # gemma_2_9b_it-lora-r64-eng-lug
[](https://huggingface.co/AfriScience-MT/gemma_2_9b_it-lora-r64-eng-lug)
This is a **LoRA adapter** for the AfriScience-MT project, enabling efficient scientific machine translation for Afric... | [
{
"start": 214,
"end": 218,
"text": "LoRA",
"label": "training method",
"score": 0.7244420647621155
},
{
"start": 571,
"end": 575,
"text": "LoRA",
"label": "training method",
"score": 0.7643969655036926
},
{
"start": 697,
"end": 701,
"text": "LoRA",
"l... |
mlx-vision/efficientnet_b5-mlxim | mlx-vision | 2025-10-25T20:03:42Z | 5 | 0 | mlx-image | [
"mlx-image",
"safetensors",
"mlx",
"vision",
"image-classification",
"dataset:imagenet-1k",
"license:apache-2.0",
"region:us"
] | image-classification | 2025-10-25T06:53:58Z | # efficientnet_b5
An EfficientNet B5 model architecture, pretrained on ImageNet-1K.
Disclaimer: this is a port of the Torchvision model weights to Apple MLX Framework.
See [mlx-convert-scripts](https://github.com/lextoumbourou/mlx-convert-scripts) repo for the conversion script used.
## How to use
```bash
pip inst... | [] |
shashika05/brain-tumor-hybrid-classifier | shashika05 | 2026-03-05T15:36:45Z | 0 | 0 | null | [
"medical",
"image-classification",
"pytorch",
"brain-tumor",
"en",
"region:us"
] | image-classification | 2026-03-05T15:31:08Z | # Hybrid Brain Tumor Classifier
This model is a Hybrid CNN-Transformer architecture (ConvNeXt + Swin Transformer) trained to classify brain MRI scans into four categories:
1. Glioma
2. Meningioma
3. No Tumor
4. Pituitary
## Performance
- **Architecture**: ConvNeXt-Tiny & Swin-Tiny Fusion
- **Test Accuracy**: ~93.46%
... | [
{
"start": 403,
"end": 413,
"text": "Focal Loss",
"label": "training method",
"score": 0.8178682327270508
},
{
"start": 459,
"end": 464,
"text": "AdamW",
"label": "training method",
"score": 0.777733564376831
}
] |
CharlesMa0915/AIA_Llama_3_2_1B_Couplet | CharlesMa0915 | 2026-04-16T06:30:01Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-1B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-04-16T06:25:19Z | # Model Card for AIA_Llama_3_2_1B_Couplet
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If ... | [] |
ijjcfs/Qwen3.5-27B-Uncensored-HauhauCS-Aggressive | ijjcfs | 2026-03-19T02:54:56Z | 914 | 0 | null | [
"gguf",
"uncensored",
"qwen3.5",
"qwen",
"en",
"zh",
"multilingual",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-19T02:54:56Z | # Qwen3.5-27B-Uncensored-HauhauCS-Aggressive
Qwen3.5-27B uncensored by HauhauCS.
## About
**0/465 refusals.** Fully uncensored with zero capability loss.
No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.
These are meant to be the best ... | [] |
rubbystar/asr_minds | rubbystar | 2025-12-23T03:44:39Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:w11wo/wav2vec2-xls-r-300m-korean",
"base_model:finetune:w11wo/wav2vec2-xls-r-300m-korean",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-12-23T03:43:37Z | <!-- 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. -->
# asr_minds
This model is a fine-tuned version of [w11wo/wav2vec2-xls-r-300m-korean](https://huggingface.co/w11wo/wav2vec2-xls-r-30... | [] |
SakaiSec/K2-Think-Q4_K_M-GGUF | SakaiSec | 2025-09-13T03:26:15Z | 9 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"base_model:LLM360/K2-Think",
"base_model:quantized:LLM360/K2-Think",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-13T03:24:01Z | # SakaiSec/K2-Think-Q4_K_M-GGUF
This model was converted to GGUF format from [`LLM360/K2-Think`](https://huggingface.co/LLM360/K2-Think) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/LLM360/K2-Think)... | [] |
PaddlePaddle/PaddleOCR-VL-1.5-GGUF | PaddlePaddle | 2026-03-06T11:31:28Z | 4,065 | 11 | null | [
"gguf",
"arxiv:2601.21957",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-26T08:10:50Z | <div align="center">
<h1 align="center">
PaddleOCR-VL-1.5: Towards a Multi-Task 0.9B VLM for Robust In-the-Wild Document Parsing
</h1>
[](https://github.com/PaddlePaddle/PaddleOCR)
[![HuggingFace](https://img.shields.io/badge/HuggingFace-... | [] |
vstrandmoe/sentiment-analysis-social-media | vstrandmoe | 2026-01-10T21:14:01Z | 1 | 0 | null | [
"safetensors",
"gpt2",
"influence-guided-training",
"dataset-curation",
"distilbert/distilgpt2",
"en",
"dataset:OdiaGenAI/sentiment_analysis_hindi",
"dataset:yassiracharki/Amazon_Reviews_Binary_for_Sentiment_Analysis",
"dataset:princeton-nlp/SWE-bench",
"dataset:racro/sentiment-analysis-finetune",... | null | 2026-01-10T19:49:57Z | # sentiment-analysis-social-media
This model was trained using **influence-guided dataset selection**, a technique that uses influence scores to identify the most impactful training data for specific concepts.
## Model Description
- **Base Model**: distilbert/distilgpt2
- **Training Concepts**: sentiment analysis, N... | [
{
"start": 397,
"end": 428,
"text": "Influence-guided data selection",
"label": "training method",
"score": 0.887681245803833
}
] |
cyberunit/gemma-3-270m-it-Q4_K_M-GGUF | cyberunit | 2025-08-22T10:14:31Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"gemma3",
"unsloth",
"gemma",
"google",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"base_model:unsloth/gemma-3-270m-it",
"base_model:quantized:unsloth/gemma-3-270m-it",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-08-22T10:14:27Z | # cyberunit/gemma-3-270m-it-Q4_K_M-GGUF
This model was converted to GGUF format from [`unsloth/gemma-3-270m-it`](https://huggingface.co/unsloth/gemma-3-270m-it) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://hugging... | [] |
inclusionAI/Ling-lite-base-1.5 | inclusionAI | 2025-05-14T00:56:56Z | 39 | 34 | transformers | [
"transformers",
"safetensors",
"bailing_moe",
"text-generation",
"conversational",
"custom_code",
"arxiv:2503.05139",
"license:mit",
"region:us"
] | text-generation | 2025-05-11T05:36:02Z | # Ling
<p align="center"><img src="https://huggingface.co/inclusionAI/Ling-lite-base/resolve/main/ant-bailing.png" width="100"/></p>
<p align="center">🤗 <a href="https://huggingface.co/inclusionAI">Hugging Face</a></p>
## Introduction
Ling is a MoE LLM provided and open-sourced by InclusionAI. We introduce two di... | [] |
Alizabethli/Qwen32_SFT_RL_claude | Alizabethli | 2025-08-14T00:49:36Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"grpo",
"trl",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-32B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-13T14:34:25Z | # Model Card for Qwen32_SFT_RL_claude
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time mac... | [] |
plotMaker/qwen25-7b-sft-merged-v5v6-a50 | plotMaker | 2026-03-02T00:20:55Z | 110 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"sft",
"agent",
"tool-use",
"alfworld",
"dbbench",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v2",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v3",
"dataset:u-10bei/sft_alfworld_trajectory_dataset... | text-generation | 2026-02-28T08:34:23Z | # qwen25-7b-sft-merged-v5v6-a50
This repository provides a **fully merged model** fine-tuned from
**Qwen2.5-7B-Instruct** using **QLoRA + Unsloth**.
Two SFT models (v5 and v6) were trained independently, then combined via
weight interpolation (alpha=0.5). This is a **complete model** — no adapters
or additional weigh... | [
{
"start": 131,
"end": 136,
"text": "QLoRA",
"label": "training method",
"score": 0.8055217266082764
},
{
"start": 139,
"end": 146,
"text": "Unsloth",
"label": "training method",
"score": 0.7914430499076843
},
{
"start": 753,
"end": 758,
"text": "QLoRA",
... |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-v2-3d-5M-500K-0.1-reverse-padzero-99-512D-3L-4H-2048I | arithmetic-circuit-overloading | 2026-04-06T20:43:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.3-70B-Instruct",
"base_model:finetune:meta-llama/Llama-3.3-70B-Instruct",
"license:llama3.3",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-06T13:26:14Z | <!-- 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. -->
# Llama-3.3-70B-Instruct-v2-3d-5M-500K-0.1-reverse-padzero-99-512D-3L-4H-2048I
This model is a fine-tuned version of [meta-llama/Ll... | [] |
WindyWord/translate-ja-ru | WindyWord | 2026-04-20T13:30:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"japanese",
"russian",
"ja",
"ru",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-18T04:32:32Z | # WindyWord.ai Translation — Japanese → Russian
**Translates Japanese → Russian.**
**Quality Rating: ⭐⭐⭐⭐½ (4.5★ Premium)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 4.5★ ⭐⭐⭐⭐½
- **Tier:** Premium
- **Comp... | [] |
introvoyz041/granite-4.0-micro-mlx-4Bit | introvoyz041 | 2025-11-29T00:07:28Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"granitemoehybrid",
"text-generation",
"language",
"granite-4.0",
"mlx",
"mlx-my-repo",
"conversational",
"base_model:ibm-granite/granite-4.0-micro",
"base_model:quantized:ibm-granite/granite-4.0-micro",
"license:apache-2.0",
"endpoints_compatible",
"4-bit",
... | text-generation | 2025-11-29T00:07:11Z | # introvoyz041/granite-4.0-micro-mlx-4Bit
The Model [introvoyz041/granite-4.0-micro-mlx-4Bit](https://huggingface.co/introvoyz041/granite-4.0-micro-mlx-4Bit) was converted to MLX format from [ibm-granite/granite-4.0-micro](https://huggingface.co/ibm-granite/granite-4.0-micro) using mlx-lm version **0.28.3**.
## Use w... | [] |
virusf/nllb-renpy-rory-v2 | virusf | 2025-08-11T17:26:14Z | 0 | 0 | null | [
"safetensors",
"m2m_100",
"translation",
"nllb",
"fine-tuned",
"gaming",
"renpy",
"visual-novel",
"en",
"fr",
"base_model:facebook/nllb-200-distilled-600M",
"base_model:finetune:facebook/nllb-200-distilled-600M",
"license:cc-by-nc-4.0",
"region:us"
] | translation | 2025-08-11T16:51:22Z | NLLB-Renpy-Rory-v2
Modèle NLLB-200 fine-tuné pour la traduction de dialogues de jeux Ren’Py (anglais → français), optimisé pour la préservation des balises et la fluidité du texte.
🚀 Utilisation rapide
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
# 📂 ID ou chemin local du modèle
MODEL_ID = "./nllb... | [] |
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