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 |
|---|---|---|---|---|---|---|---|---|---|---|
HTX-GXTEO/Nanonets-OCR-s | HTX-GXTEO | 2025-10-31T07:57:14Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"OCR",
"pdf2markdown",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-10-31T07:33:48Z | Nanonets-OCR-s by [Nanonets](https://nanonets.com) is a powerful, state-of-the-art image-to-markdown OCR model that goes far beyond traditional text extraction. It transforms documents into structured markdown with intelligent content recognition and semantic tagging, making it ideal for downstream processing by Large ... | [] |
abirmondalind/story2dialogue-SODA-T5-LoRA | abirmondalind | 2025-11-24T12:40:14Z | 0 | 0 | peft | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:google-t5/t5-base",
"base_model:adapter:google-t5/t5-base",
"license:apache-2.0",
"region:us"
] | null | 2025-11-23T14:43:59Z | <!-- 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. -->
# story2dialogue-SODA-T5-LoRA
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) o... | [] |
iRanadheer/cards_qwen3.5_9b_norecot_alpha4-lora | iRanadheer | 2026-05-03T16:41:47Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"hf_jobs",
"unsloth",
"base_model:Qwen/Qwen3.5-9B",
"base_model:finetune:Qwen/Qwen3.5-9B",
"endpoints_compatible",
"region:us"
] | null | 2026-05-03T16:02:05Z | # Model Card for cards_qwen3.5_9b_norecot_alpha4-lora
This model is a fine-tuned version of [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B).
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... | [] |
UnifiedHorusRA/Qwen_Anime_style | UnifiedHorusRA | 2025-09-10T06:06:39Z | 0 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-10T06:06:38Z | # Qwen Anime style
**Creator**: [WHYNOTFY](https://civitai.com/user/WHYNOTFY)
**Civitai Model Page**: [https://civitai.com/models/1869889](https://civitai.com/models/1869889)
---
This repository contains multiple versions of the 'Qwen Anime style' model from Civitai.
Each version's files, including a specific README... | [] |
Shuanghai/Z-Image-Turbo_fp32-fp16-bf16_comfyui | Shuanghai | 2026-04-03T06:14:55Z | 0 | 0 | diffusion-single-file | [
"diffusion-single-file",
"text-to-image",
"comfyui",
"safetensors",
"en",
"arxiv:2511.22699",
"arxiv:2511.22677",
"arxiv:2511.13649",
"base_model:Tongyi-MAI/Z-Image-Turbo",
"base_model:finetune:Tongyi-MAI/Z-Image-Turbo",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-04-03T06:14:54Z | Workflows: https://comfyanonymous.github.io/ComfyUI_examples/z_image/
```bibtex
@article{team2025zimage,
title={Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer},
author={Z-Image Team},
journal={arXiv preprint arXiv:2511.22699},
year={2025}
}
@articl... | [] |
rebirthmonkey/bart-cnn-samsum-finetuned | rebirthmonkey | 2025-09-25T06:04:53Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"generated_from_trainer",
"base_model:facebook/bart-large-cnn",
"base_model:finetune:facebook/bart-large-cnn",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-09-25T06:04:17Z | <!-- 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. -->
# bart-cnn-samsum-finetuned
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-la... | [] |
phospho-app/gr00t-dataset_4-l7z4o5h6rk | phospho-app | 2025-11-22T16:57:27Z | 0 | 0 | phosphobot | [
"phosphobot",
"safetensors",
"gr00t_n1_5",
"gr00t",
"robotics",
"dataset:rbatal/dataset_4",
"region:us"
] | robotics | 2025-11-22T16:20:02Z | ---
datasets: rbatal/dataset_4
library_name: phosphobot
pipeline_tag: robotics
model_name: gr00t
tags:
- phosphobot
- gr00t
task_categories:
- robotics
---
# gr00t model - 🧪 phosphobot training pipeline
- **Dataset**: [rbatal/dataset_4](https://huggingface.co/datasets/rbatal/dataset_4)
- **Wandb run id**: None
## ... | [] |
BilateralBusiness/perma_chef_mandil_bsico_de_peto_blanco_caballero_3_20251119_2312 | BilateralBusiness | 2025-11-19T23:29:35Z | 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 | 2025-11-19T23:28:31Z | # Perma_Chef_Camisa_Negra_Milan_Caballero_1_20251029_1647
<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: ht... | [] |
mradermacher/Seed-OSS-36B-Base-i1-GGUF | mradermacher | 2025-12-16T04:14:17Z | 7 | 0 | transformers | [
"transformers",
"gguf",
"vllm",
"en",
"base_model:ByteDance-Seed/Seed-OSS-36B-Base",
"base_model:quantized:ByteDance-Seed/Seed-OSS-36B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2025-08-25T01:44:20Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
CiroN2022/cyber-saturation-v10 | CiroN2022 | 2026-04-17T21:21:45Z | 0 | 0 | null | [
"license:other",
"region:us"
] | null | 2026-04-17T21:17:58Z | # Cyber Saturation v1.0
## 📝 Descrizione
Cyber Saturation Model, trained for 20 epochs and 1440 steps, is a specialized AI model designed to generate stunning cyberpunk portraits with saturated colors. With a focus on capturing the vibrant and energetic essence of the cyberpunk genre, this model excels at creating... | [] |
hbseong/internvla_pick_and_place_pos5_ep208_so101_ft-3ep | hbseong | 2025-11-28T14:41:51Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"internvla",
"robotics",
"dataset:hbseong/record-pick-and-place-pos5-so101",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-28T14:41:31Z | # Model Card for internvla
<!-- 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://huggingf... | [] |
sstrekozap/Credence_LoRA | sstrekozap | 2026-03-21T22:23:35Z | 3 | 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 | 2026-03-21T22:23:27Z | <!-- 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 - sstrekozap/Credence_LoRA
<Gallery />
## Model description
These are sstrekozap/Credence_LoRA Lo... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7541407346725464
},
{
"start": 318,
"end": 322,
"text": "LoRA",
"label": "training method",
"score": 0.79731684923172
},
{
"start": 465,
"end": 469,
"text": "LoRA",
"lab... |
danijo13/Qwen3-1.7B-Base-Q4_K_M-GGUF | danijo13 | 2025-10-02T04:24:22Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:Qwen/Qwen3-1.7B-Base",
"base_model:quantized:Qwen/Qwen3-1.7B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-02T04:24:13Z | # danijo13/Qwen3-1.7B-Base-Q4_K_M-GGUF
This model was converted to GGUF format from [`Qwen/Qwen3-1.7B-Base`](https://huggingface.co/Qwen/Qwen3-1.7B-Base) 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... | [] |
zatup/Affine-5FqDoGqunibzLvn6e2AW1EYV3tviZwPN4okMdJcmts3eT6MJ | zatup | 2025-08-23T12:30:18Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"vllm",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"8-bit",
"mxfp4",
"region:us"
] | text-generation | 2025-08-23T12:18:10Z | <p align="center">
<img alt="gpt-oss-120b" src="https://raw.githubusercontent.com/openai/gpt-oss/main/docs/gpt-oss-120b.svg">
</p>
<p align="center">
<a href="https://gpt-oss.com"><strong>Try gpt-oss</strong></a> ·
<a href="https://cookbook.openai.com/topic/gpt-oss"><strong>Guides</strong></a> ·
<a href="https... | [] |
cookiebasher/qwen2-7b-instruct-fine-tune-V2 | cookiebasher | 2026-03-26T12:12:55Z | 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 | 2026-03-26T11:18:11Z | # Model Card for qwen2-7b-instruct-fine-tune-V2
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 = "If you ... | [] |
Hizaneko/test2.22.2 | Hizaneko | 2026-02-22T15:40:30Z | 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 | 2026-02-22T12:16:02Z | # lora_agent_nyan2.22.2
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-turn agent ... | [
{
"start": 54,
"end": 58,
"text": "LoRA",
"label": "training method",
"score": 0.883853554725647
},
{
"start": 125,
"end": 129,
"text": "LoRA",
"label": "training method",
"score": 0.9147117137908936
},
{
"start": 171,
"end": 175,
"text": "LoRA",
"labe... |
Thireus/Qwen3.6-27B-THIREUS-Q8_K_R8-SPECIAL_SPLIT | Thireus | 2026-04-27T08:34:45Z | 0 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-04-26T05:45:10Z | # Qwen3.6-27B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.6-27B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.6-27B model (official repo: https://huggingface.co/Qwen/Qwen3.6-27B). These GGUF shards are designed to be used wit... | [] |
manu02/dialogpt-medium-bnb-4bit-nf4-dq | manu02 | 2026-02-12T02:21:09Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"quantized",
"4bit",
"bnb",
"conversational",
"en",
"base_model:microsoft/DialoGPT-medium",
"base_model:quantized:microsoft/DialoGPT-medium",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"b... | text-generation | 2026-02-12T00:23:21Z | # DialoGPT-medium (Quantized)
## Description
This model is a 4-bit quantized version of the original [`microsoft/DialoGPT-medium`](https://huggingface.co/microsoft/DialoGPT-medium) model, optimized for reduced memory usage while maintaining performance.
## Quantization Details
- **Quantization Type**: 4-bit
- ... | [] |
lightonai/LateOn-Code-edge | lightonai | 2026-02-12T13:38:12Z | 2,954 | 23 | PyLate | [
"PyLate",
"onnx",
"safetensors",
"modernbert",
"ColBERT",
"sentence-transformers",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:2117771",
"loss:Contrastive",
"code",
"embeddings",
"retrieval",
"code search",
"en",
"dataset:lightonai/nv-embed-su... | sentence-similarity | 2026-02-05T16:29:16Z | <img src="https://cdn-uploads.huggingface.co/production/uploads/609bbe2f4932693ca2009d6a/BWfClY8hoQIS_Qf9rVa__.png" width="700" height="auto">
# LateOn-Code
The [LateOn-Code collection](https://huggingface.co/collections/lightonai/lateon-code) is composed of [PyLate](https://github.com/lightonai/pylate) models optimi... | [
{
"start": 164,
"end": 175,
"text": "LateOn-Code",
"label": "training method",
"score": 0.7254620790481567
}
] |
nobana/open_and_close | nobana | 2025-09-08T02:21:29Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:nobana/open_and_close",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-08T02:21:18Z | # 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... | [] |
Muapi/my-little-pony-mlp-g5-misty-brightdawn-illustrious-and-pony | Muapi | 2025-09-03T04:32:28Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-03T04:31:48Z | # My Little Pony/MLP G5 Misty Brightdawn, Illustrious and pony
**Base model**: Flux.1 D
**Trained words**: Misty Brightdawn unicorn, blue fur and a lush mane turning from pink to purple, freckles are visible on the cheeks, It has a purple butterfly on its side., A bracelet is worn on the f... | [] |
Guilherme34/True-Qwen2.5-14B-Instruct | Guilherme34 | 2025-10-14T19:36:47Z | 27 | 4 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"grpo",
"conversational",
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-14B-Instruct"... | text-generation | 2025-10-10T19:27:18Z | <h1>**NeuroSpectr13B**</h1>(True-Qwen2.5-14B-Instruct)
Welcome to NeuroSpectr13B
NeuroSpectr13B is a large language model designed to reflect and introspect, aiming to enhance understa... | [] |
CCSSNE/trohrbaugh-gemma-4-26B-A4B-it-heretic-ara | CCSSNE | 2026-04-02T23:31:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-02T23:31:54Z | # This is a decensored version of [google/gemma-4-26B-A4B-it](https://huggingface.co/google/gemma-4-26B-A4B-it), 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
| Parameter | Valu... | [] |
lore-seri97/bert-zenotravel | lore-seri97 | 2026-02-13T13:39:51Z | 1 | 0 | null | [
"pytorch",
"bert",
"automated-planning",
"masked-language-modeling",
"license:mit",
"region:us"
] | null | 2026-02-13T13:39:41Z | # BERT for Automated Planning (Zenotravel)
This is a BERT model pretrained on Masked Language Modelling (MLM), specifically developed to tackle tasks related to Automated Planning within the Zenotravel domain.
You can find its full description, methodology, and experimental results in our paper: **[A Preliminary... | [] |
ReadyArt/Dark-Desires-22B-v1.5 | ReadyArt | 2025-10-28T15:16:39Z | 2 | 0 | null | [
"safetensors",
"mistral",
"nsfw",
"explicit",
"roleplay",
"unaligned",
"dangerous",
"ERP",
"Mistral",
"mrl",
"base_model:TheDrummer/Cydonia-Redux-22B-v1.1",
"base_model:finetune:TheDrummer/Cydonia-Redux-22B-v1.1",
"license:other",
"region:us"
] | null | 2025-10-28T15:06:38Z | <style>
body {
font-family: 'Quicksand', sans-serif;
background-color: #111; /* Darker background */
color: #fff; /* White text */
text-shadow: 0 0 5px rgba(0, 0, 0, 0.8); /* Deeper text shadow */
margin: 0;
padding: 20px;
transition: all 0.5s ease;
}
@media (prefers-color-scheme: light) {
... | [] |
Saandraahh/mistral-7b-resume-extractor-gguf | Saandraahh | 2026-01-27T17:25:20Z | 56 | 1 | null | [
"gguf",
"mistral",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-27T17:23:52Z | # mistral-7b-resume-extractor-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.cpp/llama-cli -hf Saandraahh/mistral-7b-resume-extractor-gguf --jinja`
- For multimodal models: `./llama.cpp/llama... | [
{
"start": 104,
"end": 111,
"text": "Unsloth",
"label": "training method",
"score": 0.8300813436508179
},
{
"start": 142,
"end": 149,
"text": "unsloth",
"label": "training method",
"score": 0.7901229858398438
},
{
"start": 629,
"end": 636,
"text": "Unsloth... |
masakhane/yoruba-pos-tagger-afroxlmr | masakhane | 2025-08-09T09:47:08Z | 14 | 0 | null | [
"safetensors",
"xlm-roberta",
"yo",
"base_model:Davlan/afro-xlmr-large",
"base_model:finetune:Davlan/afro-xlmr-large",
"license:apache-2.0",
"region:us"
] | null | 2025-08-09T09:43:22Z | # masakhane/yoruba-pos-tagger-afroxlmr
## Model description
**yoruba-pos-tagger-afroxlmr** is a POS tagger for Yoruba language based on [MasakhaPOS](https://github.com/masakhane-io/masakhane-pos) dataset.
## Intended uses & limitations
#### How to use
You can use this model with Transformers *pipeline* for POS.
```pyt... | [] |
derenrich/sentence-scorer | derenrich | 2026-02-07T01:38:01Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"text-classification",
"sentence-scoring",
"interestingness",
"contrastive-learning",
"siamese-network",
"endpoints-template",
"custom_handler",
"en",
"dataset:custom",
"base_model:answerdotai/ModernBERT-large",
"base_model:finetune:answerdotai/... | text-classification | 2025-12-20T20:28:01Z | # Sentence Interestingness Scorer
This model scores sentences by their "interestingness" - how compelling, notable, or attention-grabbing they are.
## Model Description
- **Task**: Sentence Scoring / Interestingness Ranking
- **Base Model**: `answerdotai/ModernBERT-large`
- **Training Method**: Contrastive learning ... | [
{
"start": 299,
"end": 319,
"text": "Contrastive learning",
"label": "training method",
"score": 0.8254263401031494
}
] |
mradermacher/Mirra-Malayalam-2-GGUF | mradermacher | 2025-12-27T00:43:36Z | 60 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen2",
"trl",
"sft",
"en",
"base_model:Praha-Labs/Mirra-Malayalam-2",
"base_model:quantized:Praha-Labs/Mirra-Malayalam-2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-27T00:39:28Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/OLMo-2-0425-1B-Instruct_gsm8k-GGUF | mradermacher | 2025-08-10T11:22:44Z | 5 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"en",
"base_model:jahyungu/OLMo-2-0425-1B-Instruct_gsm8k",
"base_model:quantized:jahyungu/OLMo-2-0425-1B-Instruct_gsm8k",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-10T11:05:40Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
aisingapore/Qwen-SEA-Guard-4B-2602 | aisingapore | 2026-02-06T01:22:44Z | 36 | 2 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"arxiv:2602.01618",
"arxiv:2512.05501",
"base_model:aisingapore/Qwen-SEA-LION-v4-4B-VL",
"base_model:finetune:aisingapore/Qwen-SEA-LION-v4-4B-VL",
"license:ot... | image-text-to-text | 2025-11-28T04:13:55Z | 
# Model Card for Qwen-SEA-Guard-4B-2602
<!-- Provide a quick summary of what the model is/does. -->
Last updated: 2026-02-04
**SEA-Guard** is a collection of safety-focused Large Language Models (LLMs) built upon the SEA-LION family, designed specifically for the Southeast Asi... | [] |
zelk12/MT7-Gen3_gemma-3-12B | zelk12 | 2025-09-24T18:52:25Z | 1 | 0 | null | [
"safetensors",
"gemma3",
"merge",
"mergekit",
"lazymergekit",
"IlyaGusev/saiga_gemma3_12b",
"zelk12/MT1-gemma-3-12B",
"soob3123/amoral-gemma3-12B-v2",
"zelk12/MT-Gen1-gemma-3-12B",
"zelk12/MT-gemma-3-12B",
"image-text-to-text",
"conversational",
"base_model:IlyaGusev/saiga_gemma3_12b",
"ba... | image-text-to-text | 2025-09-24T18:43:45Z | # MT7-Gen3_gemma-3-12B
MT7-Gen3_gemma-3-12B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [IlyaGusev/saiga_gemma3_12b](https://huggingface.co/IlyaGusev/saiga_gemma3_12b)
* [zelk12/MT1-gemma-3-12B](https://huggingface.co... | [] |
tss-deposium/mxbai-rerank-base-v2-onnx-fp16 | tss-deposium | 2026-04-05T01:42:21Z | 35 | 0 | null | [
"onnx",
"qwen2",
"reranker",
"fp16",
"cross-encoder",
"text-classification",
"base_model:mixedbread-ai/mxbai-rerank-base-v2",
"base_model:quantized:mixedbread-ai/mxbai-rerank-base-v2",
"license:apache-2.0",
"region:us"
] | text-classification | 2026-03-05T06:43:13Z | # mxbai-rerank-base-v2 — ONNX FP16
ONNX FP16 export of [mixedbread-ai/mxbai-rerank-base-v2](https://huggingface.co/mixedbread-ai/mxbai-rerank-base-v2) with the full CausalLM scoring head.
## Why this export?
The original model is a **Qwen2-0.5B CausalLM** fine-tuned for reranking (NOT a standard cross-encoder)... | [] |
rokugatsu/LLM2025_Advanced_7 | rokugatsu | 2026-03-01T08:25:26Z | 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 | 2026-02-28T19:45:47Z | # rokugatsu_qwen3-4b-agent-trajectory-lora
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 ... | [
{
"start": 73,
"end": 77,
"text": "LoRA",
"label": "training method",
"score": 0.9122463464736938
},
{
"start": 144,
"end": 148,
"text": "LoRA",
"label": "training method",
"score": 0.9288841485977173
},
{
"start": 190,
"end": 194,
"text": "LoRA",
"lab... |
mradermacher/salamandra-7b-instruct-guard-GGUF | mradermacher | 2026-03-21T20:36:49Z | 370 | 0 | transformers | [
"transformers",
"gguf",
"guardrails",
"ca",
"es",
"en",
"dataset:BSC-LT/salamandra-guard-dataset",
"base_model:BSC-LT/salamandra-7b-instruct-guard",
"base_model:quantized:BSC-LT/salamandra-7b-instruct-guard",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-21T20:06:01Z | ## 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... | [] |
Uspallata22/nexus-core | Uspallata22 | 2026-04-25T19:11:39Z | 0 | 0 | nexus-core | [
"nexus-core",
"rust",
"bare-metal",
"edge-ai",
"mcp",
"zero-copy",
"gguf",
"text-generation",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-25T18:55:16Z | # Nexus-Core × Gemma 4 (8B-IT)
## 🚀 Enterprise Integration & Strategic Acquisition
Nexus-Core represents a paradigm shift in bare-metal Edge AI orchestration. By collapsing the Python GIL bottleneck through a zero-copy Rust core, eliminating PagedAttention VRAM fragmentation via reference-counted Copy-on-Write KV bl... | [] |
Nico78567/finetuning-sentiment-model-3000-samples | Nico78567 | 2025-09-10T09:31:21Z | 0 | 0 | null | [
"safetensors",
"distilbert",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"region:us"
] | null | 2025-09-10T09:28:46Z | <!-- 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. -->
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | [] |
Pilipdagh/codegen-6B-multi | Pilipdagh | 2026-04-15T18:18:59Z | 0 | 0 | null | [
"pytorch",
"codegen",
"arxiv:2203.13474",
"license:bsd-3-clause",
"region:us"
] | null | 2026-04-15T18:18:58Z | # CodeGen (CodeGen-Multi 6B)
## Model description
CodeGen is a family of autoregressive language models for **program synthesis** from the paper: [A Conversational Paradigm for Program Synthesis](https://arxiv.org/abs/2203.13474) by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savar... | [
{
"start": 11,
"end": 27,
"text": "CodeGen-Multi 6B",
"label": "training method",
"score": 0.8648949265480042
},
{
"start": 610,
"end": 626,
"text": "CodeGen-Multi 6B",
"label": "training method",
"score": 0.9153212308883667
},
{
"start": 694,
"end": 707,
... |
cveavy/Affine-cvea4-5HB8q6Bs6hxzwDXUFRhmHmiMFxWRZ4VZ3Cbt6XfG1g4GeH9r | cveavy | 2026-01-15T17:05:54Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"affine",
"causal-lm",
"reasoning",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-15T17:05:22Z | # Model Card
## Description
A Qwen3-based language model (~7B parameters) optimized for the Affine network. Features a 40K token context window, 36 transformer layers, and efficient grouped query attention (GQA) architecture. Designed for high-performance reasoning, code generation, and agentic AI applications.
## W... | [] |
CiroN2022/graphite-precision-fx-flux-v10 | CiroN2022 | 2026-04-19T18:11:49Z | 0 | 0 | null | [
"license:other",
"region:us"
] | null | 2026-04-19T18:08:57Z | # Graphite Precision FX Flux v1.0
## 📝 Descrizione
Graphite Precision FX is a LoRA model designed to generate pencil drawings with exceptional precision, perfect for capturing every detail with fine lines and smooth shading. Ideal for those looking for a realistic illustrative style but with the elegance of a manu... | [] |
mradermacher/Synth-2-GGUF | mradermacher | 2025-09-15T07:16:54Z | 11 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:LucidityAI/Synth-2",
"base_model:quantized:LucidityAI/Synth-2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-15T06:48:26Z | ## 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... | [] |
jialicheng/unlearn-cl_cifar10_swin-base_salun_8_42 | jialicheng | 2025-10-27T02:30:10Z | 10 | 0 | transformers | [
"transformers",
"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",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-10-27T02:28:42Z | <!-- 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. -->
# 42
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patc... | [] |
hemlang/Hemlock2-Coder-7B | hemlang | 2026-04-14T16:23:48Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"merlina",
"grimoire",
"orpo",
"conversational",
"dataset:hemlang/Hemlock2-DPO",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-Coder-7B-Instruct",
"text-generation-inference",
"endpoints_compatible",
... | text-generation | 2026-04-14T14:31:44Z | 
# Hemlock2-Coder-7B
## Training Configuration
| Parameter | Value |
|-----------|-------|
| Training Mode | ORPO |
| Base Model | `Qwen/Qwen2.5-Coder-7B-Instruct` |
| Learning Rate | 9e-05 |
| Epochs | 2 |
| Batch S... | [] |
tensorblock/kamelcharaf_GRPO-qwen2.5-7B-qwen2.5-7B-mrd3-s7-sum_token_prompt-merged-GGUF | tensorblock | 2026-01-27T20:56:10Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"TensorBlock",
"GGUF",
"base_model:kamelcharaf/GRPO-qwen2.5-7B-qwen2.5-7B-mrd3-s7-sum_token_prompt-merged",
"base_model:quantized:kamelcharaf/GRPO-qwen2.5-7B-qwen2.5-7B-mrd3-s7-sum_token_prompt-merged",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-17T20:20:16Z | <div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
[](https://t... | [] |
lmstudio-community/Qwen3-VL-32B-Instruct-MLX-4bit | lmstudio-community | 2025-10-28T14:00:51Z | 798 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"mlx",
"conversational",
"base_model:Qwen/Qwen3-VL-32B-Instruct",
"base_model:quantized:Qwen/Qwen3-VL-32B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"4-bit",
"region:us"
] | image-text-to-text | 2025-10-21T16:24:21Z | ## 💫 Community Model> Qwen3-VL-32B-Instruct by Qwen
_👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)_.
**Model creator**: [Qwen](https://huggingface.co/Qwen)<br>
**Origina... | [] |
CnLori/act_so101_pickup_cube | CnLori | 2025-09-23T04:27:22Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:CnLori/so101_pickup_cube",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-23T04:27:03Z | # 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":... |
AnonymousCS/populism_classifier_bsample_384 | AnonymousCS | 2025-08-28T04:26:44Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_english_bert_large_uncased",
"base_model:finetune:AnonymousCS/populism_english_bert_large_uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2025-08-28T04:25:35Z | <!-- 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_bsample_384
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://h... | [] |
xianyudesuiyue/stable-diffusion-xl-base-1.0 | xianyudesuiyue | 2026-05-02T11:08:34Z | 0 | 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 | 2026-05-02T11:08:32Z | # 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 ... | [] |
noisyduck/act_conveyor_ours_250918_4_5 | noisyduck | 2025-09-19T03:49:36Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:noisyduck/ours_conveyor_downsampled_ours_250918_4_5",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-19T03:49:22Z | # 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": 0.8059530854225159
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8365488052368164
},
{
"start": 883,
"end": 886,
"text": "act",
"label"... |
tkan/qwen6 | tkan | 2026-02-21T09:23:15Z | 0 | 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 | 2026-02-21T09:22:55Z | qwen3-4b-structured-output-lora-tkan6
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 impro... | [
{
"start": 139,
"end": 144,
"text": "QLoRA",
"label": "training method",
"score": 0.7769716382026672
}
] |
InstaDeepAI/instanovo-v1.0.0 | InstaDeepAI | 2025-10-09T11:17:28Z | 6 | 0 | pytorch | [
"pytorch",
"safetensors",
"proteomics",
"mass-spectrometry",
"peptide-sequencing",
"de-novo-sequencing",
"transformer",
"biology",
"computational-biology",
"text-generation",
"dataset:InstaDeepAI/ms_ninespecies_benchmark",
"dataset:InstaDeepAI/ms_proteometools",
"license:cc-by-nc-sa-4.0",
... | text-generation | 2025-10-08T15:04:31Z | # InstaNovo: De novo Peptide Sequencing Model
## Model Description
InstaNovo is a state-of-the-art transformer-based model for de novo peptide sequencing from mass spectrometry data. This model enables accurate, database-free peptide identification for large-scale proteomics experiments. InstaNovo uses a transformer a... | [] |
ryo-llm/qwen3-4b-agent-trajectory-lora-202603011856 | ryo-llm | 2026-03-01T10:18:08Z | 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 | 2026-03-01T10:17:03Z | # ryo-llm/qwen3-4b-agent-trajectory-lora-202603011856
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 ... | [
{
"start": 84,
"end": 88,
"text": "LoRA",
"label": "training method",
"score": 0.9034468531608582
},
{
"start": 155,
"end": 159,
"text": "LoRA",
"label": "training method",
"score": 0.9226826429367065
},
{
"start": 201,
"end": 205,
"text": "LoRA",
"lab... |
BrejBala/DogBreedClassification | BrejBala | 2025-12-13T04:21:25Z | 0 | 0 | tensorflow | [
"tensorflow",
"keras",
"tensorflow-hub",
"mobilenetv2",
"transfer-learning",
"computer-vision",
"image-classification",
"multi-class-classification",
"dog-breed-classification",
"kaggle-competition",
"en",
"license:mit",
"model-index",
"region:us"
] | image-classification | 2025-12-13T04:16:20Z | # 🐶 Dog Breed Classification (TensorFlow Hub MobileNetV2)
This model predicts the **dog breed (120 classes)** from an input image using **transfer learning** with a pretrained **MobileNetV2** model from **TensorFlow Hub**, plus a custom dense softmax classifier head.
It is built as an end-to-end computer vision pipe... | [
{
"start": 139,
"end": 156,
"text": "transfer learning",
"label": "training method",
"score": 0.855338990688324
},
{
"start": 1098,
"end": 1115,
"text": "transfer learning",
"label": "training method",
"score": 0.8008870482444763
}
] |
contemmcm/da9f71c7bd95ffef980859926c3fdb5a | contemmcm | 2025-11-19T06:00:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"luke",
"text-classification",
"generated_from_trainer",
"base_model:studio-ousia/mluke-base",
"base_model:finetune:studio-ousia/mluke-base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-19T05:45:34Z | <!-- 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. -->
# da9f71c7bd95ffef980859926c3fdb5a
This model is a fine-tuned version of [studio-ousia/mluke-base](https://huggingface.co/studio-ou... | [] |
Patoni31/4 | Patoni31 | 2026-04-06T19:29:32Z | 0 | 0 | null | [
"region:us"
] | null | 2026-04-06T19:27:07Z | # Wild Tokyo Promo Code TOKYOWELCOME26 Get 260% up to €3000 plus 620 Free Spins
Wild Tokyo brings a dynamic casino experience with a strong focus on bonuses and themed gameplay. This page explains how to use the Wild Tokyo promo code TOKYOWELCOME26 to unlock a 260% bonus up to €3000 plus 620 Free Spins. The offer is d... | [] |
p1atdev/dart-v2-moe-sft | p1atdev | 2024-05-11T17:27:21Z | 1,607 | 16 | transformers | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"trl",
"sft",
"optimum",
"danbooru",
"dataset:isek-ai/danbooru-tags-2024",
"base_model:p1atdev/dart-v2-moe-base",
"base_model:finetune:p1atdev/dart-v2-moe-base",
"license:apache-2.0",
"text-generation-inference",
"deploy:azure",
... | text-generation | 2024-05-06T08:39:50Z | # Dart (Danbooru Tags Transformer) v2
This model is a fine-tuned Dart (Danbooru Tags Transformer) model that generates danbooru tags.
Demo: [🤗 Space with ZERO](https://huggingface.co/spaces/p1atdev/danbooru-tags-transformer-v2)
## Model variants
|Name|Architecture|Param size|Type|
|-|-|-|-|
|[v2-moe-sft](https://h... | [] |
Nbeau/qwen-swan-sig-2b | Nbeau | 2026-05-01T03:29:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"code",
"swan",
"scade",
"lustre",
"signature-prediction",
"ide-assistant",
"qwen",
"lora",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen3.5-2B",
"base_model:adapter:Qwen/Qwen3.5-2B",
"license:apache... | text-generation | 2026-04-30T19:16:03Z | # qwen-swan-sig-2b
Fine-tuned **Qwen3.5-2B** lightweight variant of [`Nbeau/qwen-swan-sig-4b`](https://huggingface.co/Nbeau/qwen-swan-sig-4b), for the same Swan / SCADE / Lustre signature-prediction task. Use this model when **inference cost or on-device deployment** matters (~4 GB bf16, ~1.5 GB at INT4).
## Task... | [] |
haikalmumtaz/facenet-onnx | haikalmumtaz | 2025-11-07T08:07:31Z | 1 | 0 | null | [
"onnx",
"endpoints_compatible",
"region:us"
] | null | 2025-10-28T10:35:06Z | # Face Embedding Model (ONNX)
This model converts a cropped face image into a 512-dimensional embedding vector.
Ideal for event-based photo matching or identity-aware photo search systems.
**Framework:** ONNX
**Task:** Feature Extraction
**Output:** 512-dimensional float vector
## Example Usage
```bash
curl -X P... | [] |
osieosie/Qwen2_5-7B-Instruct_qwen2_5-7b-s1k-sft-gemini-full-s42-e1-lr2e_5 | osieosie | 2026-01-20T23:07:54Z | 1 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-20T23:07:18Z | # Model Card for Qwen2.5-7B-Instruct_20251017_qwen2.5-7b-s1k-sft-gemini-full-s42-e3-lr2e-5
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers... | [] |
STMicroelectronics/regnet_pt | STMicroelectronics | 2026-01-22T17:53:40Z | 0 | 0 | null | [
"image-classification",
"arxiv:2003.13678",
"license:apache-2.0",
"region:us"
] | image-classification | 2026-01-22T17:53:00Z | # RegNet
## **Use case** : `Image classification`
# Model description
RegNet introduces a **design space paradigm** for neural networks. Rather than designing individual architectures, RegNet defines a design space of possible networks characterized by a few parameters, enabling systematic exploration of network de... | [] |
MLLM-CL/MRLoRA_Experts | MLLM-CL | 2025-10-03T13:37:43Z | 0 | 0 | transformers | [
"transformers",
"finance",
"medical",
"AD",
"MLLM-CL",
"Sci",
"RS",
"Math",
"OCR",
"Count",
"GUI-Agent",
"DCL",
"ACL",
"llava",
"multimodal",
"image-to-text",
"text-generation",
"image-text-to-text",
"en",
"dataset:MLLM-CL/MLLM-CL",
"dataset:MLLM-CL/MLLM-CL-ReplayData",
"ar... | image-text-to-text | 2025-09-29T08:26:58Z | ## MLLM-CL Benchmark Description
MLLM-CL is a novel benchmark encompassing domain and ability continual learning, where the former focuses on independently and identically distributed (IID) evaluation across evolving mainstream domains,
whereas the latter evaluates on non-IID scenarios with emerging model ability.
For... | [] |
mradermacher/zen3-embedding-small-GGUF | mradermacher | 2026-02-28T22:15:04Z | 322 | 0 | transformers | [
"transformers",
"gguf",
"feature-extraction",
"zen",
"zenlm",
"hanzo",
"zen3",
"embedding",
"retrieval",
"en",
"base_model:zenlm/zen3-embedding-small",
"base_model:quantized:zenlm/zen3-embedding-small",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2026-02-24T20:57:54Z | ## 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... | [] |
rockon1095/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-Q4_0-GGUF | rockon1095 | 2025-10-13T12:10:50Z | 39 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"llama-3",
"llama-3.2",
"llama-cpp",
"gguf-my-repo",
"base_model:DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B",
"base_model:quantized:DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B",
"e... | null | 2025-10-13T12:10:03Z | # rockon1095/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-Q4_0-GGUF
This model was converted to GGUF format from [`DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B`](https://huggingface.co/DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18... | [] |
ericson333/csound_black_female | ericson333 | 2025-09-20T06:27:37Z | 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 | 2025-09-20T06:04:47Z | # Csound_Black_Female
<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-... | [] |
OpenMed/OpenMed-PII-German-ClinicalE5-Large-335M-v1-mlx | OpenMed | 2026-04-14T07:43:34Z | 0 | 0 | openmed | [
"openmed",
"bert",
"mlx",
"apple-silicon",
"token-classification",
"pii",
"de-identification",
"medical",
"clinical",
"base_model:OpenMed/OpenMed-PII-German-ClinicalE5-Large-335M-v1",
"base_model:finetune:OpenMed/OpenMed-PII-German-ClinicalE5-Large-335M-v1",
"license:apache-2.0",
"region:us"... | token-classification | 2026-04-08T19:31:04Z | # OpenMed-PII-German-ClinicalE5-Large-335M-v1 for OpenMed MLX
This repository contains an MLX packaging of [`OpenMed/OpenMed-PII-German-ClinicalE5-Large-335M-v1`](https://huggingface.co/OpenMed/OpenMed-PII-German-ClinicalE5-Large-335M-v1) for Apple Silicon inference with [OpenMed](https://github.com/maziyarpanahi/open... | [] |
keras/dfine_large_coco | keras | 2026-02-26T22:21:02Z | 10 | 0 | keras-hub | [
"keras-hub",
"arxiv:2410.13842",
"region:us"
] | null | 2025-10-27T16:47:03Z | ### Model Overview
# Model Summary
D-FINE is a family of lightweight, real-time object detection models built on the DETR (DEtection TRansformer) architecture. It achieves outstanding localization precision by redefining the bounding box regression task. D-FINE is a powerful object detector designed for a wide range o... | [] |
mradermacher/Nix-2.7a-GGUF | mradermacher | 2026-04-13T00:50:02Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Nix-ai/Nix-2.7a",
"base_model:quantized:Nix-ai/Nix-2.7a",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-13T00:33:42Z | ## 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... | [] |
willopcbeta/lite-whisper-large-v3-turbo | willopcbeta | 2026-04-14T11:33:41Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"arxiv:2502.20583",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-04-14T09:00:05Z | # Model Card for Lite-Whisper large-v3-turbo
<!-- Provide a quick summary of what the model is/does. -->
Lite-Whisper is a compressed version of OpenAI Whisper with LiteASR. See our [GitHub repository](https://github.com/efeslab/LiteASR) and [paper](https://arxiv.org/abs/2502.20583) for details.
## Benchmark Results... | [] |
mradermacher/Apertus-8b-instruct-patched-GGUF | mradermacher | 2025-12-21T23:08:10Z | 49 | 2 | transformers | [
"transformers",
"gguf",
"multilingual",
"compliant",
"swiss-ai",
"apertus",
"en",
"base_model:NewEden/Apertus-8b-instruct-patched",
"base_model:quantized:NewEden/Apertus-8b-instruct-patched",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-20T17:20:03Z | ## 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... | [] |
manthilaffs/Gamunu-4B-Instruct-Alpha-GGUF | manthilaffs | 2025-11-04T18:29:05Z | 230 | 0 | null | [
"gguf",
"instruction-following",
"NLP",
"question-answering",
"reasoning",
"academic",
"LK",
"llama-cpp",
"text-generation",
"si",
"en",
"base_model:manthilaffs/Gamunu-4B-Instruct-Alpha",
"base_model:quantized:manthilaffs/Gamunu-4B-Instruct-Alpha",
"license:apache-2.0",
"endpoints_compat... | text-generation | 2025-11-01T08:06:06Z | # manthilaffs/Gamunu-4B-Instruct-Alpha-GGUF
These models was converted to GGUF format from [`manthilaffs/Gamunu-4B-Instruct-Alpha`](https://huggingface.co/manthilaffs/Gamunu-4B-Instruct-Alpha) using llama.cpp.
Refer to the [original model card](https://huggingface.co/manthilaffs/Gamunu-4B-Instruct-Alpha) for more detai... | [] |
manoaad/book-cover-lora-v1-f | manoaad | 2026-04-12T14:42:30Z | 0 | 0 | peft | [
"peft",
"safetensors",
"lora",
"text-to-image",
"stable-diffusion",
"stable-diffusion-diffusers",
"book-covers",
"creative-design",
"mdjrny-v4",
"base_model:runwayml/stable-diffusion-v1-5",
"base_model:adapter:runwayml/stable-diffusion-v1-5",
"license:openrail++",
"region:us"
] | text-to-image | 2026-04-12T14:35:13Z | # 📚 Book Cover LoRA Adapter (Stable Diffusion 1.5)
A lightweight LoRA (Low-Rank Adaptation) adapter fine-tuned on the `marvy/book-covers` dataset to generate **professional, publication-ready book covers** using Stable Diffusion 1.5. Optimized for centered compositions, title-safe zones, and the `mdjrny-v4` aesthetic... | [] |
pyromind/Qwen3-VL-4B-Instruct-Geometry3k | pyromind | 2026-03-04T10:06:39Z | 19 | 0 | null | [
"safetensors",
"qwen3_vl",
"arxiv:2402.03300",
"arxiv:2308.12966",
"region:us"
] | null | 2026-03-04T10:04:54Z | # Qwen3-VL-4B-Instruct Geometry3K Model
This directory contains a Qwen3-VL-4B-Instruct model trained using **SFT (Supervised Fine-Tuning) + RL (Reinforcement Learning)** methods, specifically optimized for the Geometry3K geometric reasoning task.
## Model Information
- **Base Model**: [Qwen3-VL-4B-Instruct](https://... | [] |
Dartfade/google-t5-samsum-demo-ik | Dartfade | 2026-02-25T19:40:03Z | 14 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"base_model:finetune:google-t5/t5-small",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2026-02-25T19:29:55Z | <!-- 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. -->
# google-t5-samsum-demo-ik
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on... | [] |
FlameF0X/LFM2.5-1.2B-Distilled-Claude | FlameF0X | 2026-04-09T15:44:49Z | 1,796 | 2 | transformers | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"liquid",
"reasoning",
"cot",
"distillate",
"conversational",
"en",
"dataset:TeichAI/Claude-Opus-4.6-Reasoning-500x",
"dataset:TeichAI/Claude-Sonnet-4.6-Reasoning-1100x",
"dataset:TeichAI/claude-4.5-opus-high-reasoning-250x",
"datas... | text-generation | 2026-04-05T22:39:22Z | <div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6615494716917dfdc645c44e/IKWKAsS9DFnGoFCmYNQYs.png" alt="Liquid Claude" style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em; reading-order: 20px; border-radius: 20px;"/>... | [] |
itazap/blt-1b-hf | itazap | 2025-09-19T12:10:48Z | 14,698 | 5 | null | [
"safetensors",
"blt",
"arxiv:2412.09871",
"license:apache-2.0",
"region:us"
] | null | 2025-08-14T16:56:26Z | # Byte Latent Transformer (BLT)
## Model Description
**BLT (Byte Latent Transformer)** is a tokenizer-free transformer architecture that operates directly on raw byte sequences. Instead of processing text token by token, BLT dynamically groups bytes into **entropy-... | [] |
Thireus/GLM-4.5-Air-THIREUS-IQ1_BN-SPECIAL_SPLIT | Thireus | 2026-02-12T07:06:52Z | 21 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-08-04T05:08:29Z | # GLM-4.5-Air
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/GLM-4.5-Air-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the GLM-4.5-Air model (official repo: https://huggingface.co/zai-org/GLM-4.5-Air). These GGUF shards are designed to be used ... | [] |
jockey1011/Qwen3-4b-thinking-abliterated | jockey1011 | 2026-01-12T23:33:12Z | 12 | 1 | gguf | [
"gguf",
"qwen",
"qwen3",
"reasoning",
"thinking",
"uncensored",
"abliterated",
"code",
"en",
"base_model:Qwen/Qwen3-4B-Thinking-2507",
"base_model:quantized:Qwen/Qwen3-4B-Thinking-2507",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-31T03:41:14Z | # Qwen3-4b-thinking-abliterated (GGUF)
This is a surgically modified version of **Qwen3-4B-Thinking-2507**,
It combines **Native Reasoning (Chain-of-Thought)** with **Full Compliance (Uncensored)** through mathematical ablation.
### 🧠 Model DNA
* **Base Model:** [Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen... | [] |
irisaparina/IntentRL-Ambig-Text2SQL-4B | irisaparina | 2026-02-13T18:35:00Z | 10 | 0 | null | [
"safetensors",
"qwen3",
"text-to-sql",
"ambiguity",
"reinforcement-learning",
"grpo",
"en",
"arxiv:2511.10453",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:mit",
"region:us"
] | reinforcement-learning | 2026-02-13T18:31:58Z | # IntentRL-Ambig-Text2SQL-4B
This model is trained to handle **ambiguous text-to-SQL requests** by explicitly reasoning about user intent and producing multiple interpretation–answer pairs rather than silently committing to a single interpretation.
It is based on [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Q... | [
{
"start": 367,
"end": 369,
"text": "RL",
"label": "training method",
"score": 0.7629250288009644
},
{
"start": 1267,
"end": 1269,
"text": "RL",
"label": "training method",
"score": 0.7770647406578064
},
{
"start": 1543,
"end": 1551,
"text": "intentRL",
... |
Dracoform/Qwen2.5-14B-Instruct-1M-abliterated-mlx-8Bit | Dracoform | 2026-01-28T11:18:53Z | 109 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"abliterated",
"uncensored",
"mlx",
"mlx-my-repo",
"conversational",
"en",
"base_model:huihui-ai/Qwen2.5-14B-Instruct-1M-abliterated",
"base_model:quantized:huihui-ai/Qwen2.5-14B-Instruct-1M-abliterated",
"license:apache-2.... | text-generation | 2026-01-28T11:17:11Z | # Dracoform/Qwen2.5-14B-Instruct-1M-abliterated-mlx-8Bit
The Model [Dracoform/Qwen2.5-14B-Instruct-1M-abliterated-mlx-8Bit](https://huggingface.co/Dracoform/Qwen2.5-14B-Instruct-1M-abliterated-mlx-8Bit) was converted to MLX format from [huihui-ai/Qwen2.5-14B-Instruct-1M-abliterated](https://huggingface.co/huihui-ai/Qw... | [] |
asparius/Qwen3-14B-GRPO-1ep-iter8 | asparius | 2025-12-29T17:46:46Z | 7 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"open-r1",
"conversational",
"dataset:DigitalLearningGmbH/MATH-lighteval",
"arxiv:2402.03300",
"base_model:Qwen/Qwen3-14B-Base",
"base_model:finetune:Qwen/Qwen3-14B-Base",
"text-generation-inference",
"endpo... | text-generation | 2025-12-29T17:42:20Z | # Model Card for None
This model is a fine-tuned version of [Qwen/Qwen3-14B-Base](https://huggingface.co/Qwen/Qwen3-14B-Base) on the [DigitalLearningGmbH/MATH-lighteval](https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
##... | [] |
AleksanderObuchowski/whisper-large-v3-turbo-med-pl-lora-r64-enc-dec-lr2e-04-ep5-whisper_fair | AleksanderObuchowski | 2026-04-07T19:55:40Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:openai/whisper-large-v3-turbo",
"lora",
"transformers",
"pl",
"base_model:openai/whisper-large-v3-turbo",
"license:mit",
"region:us"
] | null | 2026-04-03T17:35:56Z | <!-- 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. -->
# whisper-large-v3-turbo-med-pl-lora-r64-enc-dec-lr2e-04-ep5-whisper_fair
This model is a fine-tuned version of [openai/whisper-lar... | [] |
cfierro/llama-3.1-8b-sdft-5e-6lr | cfierro | 2026-03-10T08:10:27Z | 23 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | 2026-03-10T08:03:33Z | # llama-3.1-8b-sdft-5e-6lr
## Training Hyperparameters
| Parameter | Value |
|---|---|
| learning_rate | 5e-06 |
| num_train_epochs | 1 |
| per_device_train_batch_size | 1 |
| gradient_accumulation_steps | 2 |
| weight_decay | 0.0 |
| warmup_ratio | 0.03 |
| warmup_steps | 0 |
| lr_scheduler_type | SchedulerType.CONS... | [] |
Muapi/experimental-photography-flux | Muapi | 2025-08-22T03:33:15Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-22T03:33:02Z | # Experimental Photography [FLUX]
**Base model**: Flux.1 D
**Trained words**: aidmaExperimentalPhotography
## 🧠 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_l... | [] |
zacdan4801/wav2vec2-lv-60-espeak-cv-ft-DisorderedSpeech-f5 | zacdan4801 | 2026-03-05T09:24:20Z | 163 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/wav2vec2-lv-60-espeak-cv-ft",
"base_model:finetune:facebook/wav2vec2-lv-60-espeak-cv-ft",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-03-03T07:03:17Z | <!-- 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. -->
# wav2vec2-lv-60-espeak-cv-ft-DisorderedSpeech-f5
This model is a fine-tuned version of [facebook/wav2vec2-lv-60-espeak-cv-ft]... | [] |
magicunicorn/whisper-large-v2-amd-npu-int8 | magicunicorn | 2025-08-30T18:14:01Z | 4 | 5 | unicorn-engine | [
"unicorn-engine",
"whisper",
"asr",
"speech-recognition",
"npu",
"amd",
"int8",
"quantized",
"edge-ai",
"en",
"dataset:openai/librispeech_asr",
"license:mit",
"model-index",
"region:us"
] | null | 2025-08-30T18:14:00Z | # Whisper LARGE-V2 - AMD NPU Optimized
🚀 **180x Faster than CPU** | 🎯 **98% Accuracy** | ⚡ **10W Power**
## Overview
Whisper Large-v2 optimized for AMD NPU - proven in production
This model is part of the **Unicorn Execution Engine**, a revolutionary runtime that unlocks the full potential of modern NPUs through ... | [] |
Shoriful025/medcaption-vif-clip | Shoriful025 | 2025-12-15T09:07:52Z | 0 | 0 | null | [
"region:us"
] | null | 2025-12-15T09:06:47Z | # medcaption-vif-clip
## Model Overview
The `medcaption-vif-clip` model is a **Vision-Language Model (VLM)** designed specifically for **Medical Image Captioning**. It takes a medical scan image (e.g., X-ray, MRI, CT) as input and generates a descriptive, clinically relevant natural language caption/summary. This mod... | [] |
hosyan/lora_structeval_t_qwen3_4b_alldataset_cleanv6 | hosyan | 2026-03-01T10:54:13Z | 8 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:hosyan/merged_alldataset_clean_v1",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-01T10:53:52Z | lora_structeval_t_qwen3_4b_alldataset_clean_epoc3-lr3e-5-loraalpha-64drop0.05
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 Obj... | [
{
"start": 179,
"end": 184,
"text": "QLoRA",
"label": "training method",
"score": 0.7919012904167175
}
] |
starsfriday/Kontext-Mythical-LoRA | starsfriday | 2025-09-23T01:55:15Z | 8 | 1 | diffusers | [
"diffusers",
"image-generation",
"lora",
"kontext",
"image-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-Kontext-dev",
"base_model:adapter:black-forest-labs/FLUX.1-Kontext-dev",
"license:apache-2.0",
"region:us"
] | image-to-image | 2025-09-23T01:51:12Z | # starsfriday Kontext Dev LoRA
<Gallery />
## Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This is a model for style transfer, trained on ```black-forest-labs/FLUX.1-Kontext-dev```, and it is mainly used to generate male and female costumes in the ancient Chinese immortal and ... | [] |
mradermacher/FaithLens-GGUF | mradermacher | 2025-12-24T15:28:12Z | 12 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:ssz1111/FaithLens",
"base_model:quantized:ssz1111/FaithLens",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-24T13:43:37Z | ## 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... | [] |
lukexue07/stigmatizing_detector | lukexue07 | 2025-12-23T02:02:54Z | 0 | 0 | null | [
"safetensors",
"bert",
"en",
"license:mit",
"region:us"
] | null | 2025-12-02T04:51:19Z | ## Overview
This model can be used to evaluate how well doctors are adhereing to proper clinical documentation practices. It specifically analyzes their text for uses of stigmatizing language.
## Background
When documenting their patient's conditions, doctors are trained to eliminate the use of stigmatizing languag... | [] |
jahyungu/Qwen2.5-Math-7B-Instruct-Humanities | jahyungu | 2026-02-25T07:57:07Z | 12 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-Math-7B-Instruct",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen2.5-Math-7B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-25T07:51:09Z | <!-- 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. -->
# Qwen2.5-Math-7B-Instruct-Humanities
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B-Instruct](https://huggingface.co/... | [] |
mradermacher/Qwen3-Research-Thinker-i1-GGUF | mradermacher | 2026-01-23T18:59:51Z | 38 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:beyoru/Qwen3-Research-Thinker",
"base_model:quantized:beyoru/Qwen3-Research-Thinker",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-23T15:48:53Z | ## 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_... | [] |
guhantech/CipherModel-1.5B | guhantech | 2026-04-30T14:32:08Z | 7 | 0 | gguf | [
"gguf",
"code",
"coding-assistant",
"llama-cpp",
"ciphercode",
"vscode",
"developer-tools",
"text-generation",
"en",
"arxiv:2409.12186",
"base_model:Qwen/Qwen2.5-Coder-1.5B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-Coder-1.5B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"... | text-generation | 2026-04-30T14:25:21Z | # CipherModel-1.5B
> **Your IDE's new best friend.**
> The model behind [CipherCode](https://huggingface.co/guhantech) — the AI coding assistant that learns *your* style, remembers *your* projects, and writes code in *your* voice.
>
> By **Lila AI LLC** · Closed beta v0.1
---
## What CipherCode Delivers
CipherCode ... | [] |
mmis1000/asmr-qwen3.5-9b-zh-tw-echo-gguf-v0.1 | mmis1000 | 2026-03-31T19:26:47Z | 105 | 0 | null | [
"gguf",
"asmr",
"translation",
"japanese",
"chinese",
"text-generation",
"ja",
"zh",
"base_model:unsloth/Qwen3.5-9B",
"base_model:quantized:unsloth/Qwen3.5-9B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-03-31T19:22:02Z | # asmr-qwen3.5-9b-zh-tw-echo-gguf-v0.1
GGUF quantizations of a fine-tuned model for translating Japanese ASMR transcriptions (ASR/Whisper output) into **Traditional Chinese**.
The model normalizes imperfect audio transcriptions, applies domain-specific glossaries, and translates character dialogue while retaining emo... | [] |
manancode/opus-mt-es-et-ctranslate2-android | manancode | 2025-08-17T16:38:44Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-17T16:38:34Z | # opus-mt-es-et-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-es-et` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-es-et
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted by*... | [] |
qing-yao/relfreq_n5000_nb150k_70m_ep5_lr1e-4_seed42 | qing-yao | 2025-12-27T09:09:30Z | 0 | 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 | 2025-12-27T09:09:02Z | <!-- 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_n5000_nb150k_70m_ep5_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://huggingface.co/E... | [] |
mradermacher/Gliese-OCR-7B-Post1.0-i1-GGUF | mradermacher | 2025-12-07T20:17:46Z | 137 | 1 | transformers | [
"transformers",
"gguf",
"Document",
"VLM",
"OCR",
"VL",
"Camel",
"Openpdf",
"text-generation-inference",
"Extraction",
"Linking",
"Markdown",
"Document Digitization",
"Intelligent Document Processing (IDP)",
"Intelligent Word Recognition (IWR)",
"Optical Mark Recognition (OMR)",
"en"... | null | 2025-09-13T09:46:46Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
sharkdodo/Indic-Bert-NER-Model | sharkdodo | 2026-04-24T09:23:07Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"albert",
"token-classification",
"ner",
"named-entity-recognition",
"indic-languages",
"bert",
"medical-nlp",
"regulatory",
"pharmaceutical",
"en",
"dataset:sharkdodo/Indic-Bert-NER-BIO-Dataset",
"base_model:ai4bharat/indic-bert",
"base_model:finetune:ai4b... | token-classification | 2026-04-24T07:19:25Z | # Indic-Bert-NER-Model
A fine-tuned Named Entity Recognition (NER) model based on [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) for extracting medical and regulatory entities from Indian language documents.
## Model Details
### Overview
This model is fine-tuned for NER tasks on medical and regu... | [] |
Kazchoko/bci-stage2-tfe-llama-checkpoints | Kazchoko | 2026-02-23T21:48:39Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-02-23T21:48:28Z | # Model Card for bci-stage2-tfe-llama-checkpoints
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
questio... | [] |
Jackrong/MLX-Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-8bit | Jackrong | 2026-03-19T00:15:54Z | 549 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"lora",
"text-generation",
"conversational",
"en",
"zh",
"ko",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtered",
"dataset:Jackrong/Qwen3.5-reasoning-700x",
"dataset:Roman1111111/claude-... | text-generation | 2026-03-19T00:08:24Z | # Jackrong/MLX-Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-8bit
This model [Jackrong/MLX-Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-8bit](https://huggingface.co/Jackrong/MLX-Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-8bit) was
converted to MLX format from [Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reason... | [] |
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