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 |
|---|---|---|---|---|---|---|---|---|---|---|
isuruwijesiri/all-MiniLM-L6-v2-code-search-512 | isuruwijesiri | 2026-01-05T09:35:40Z | 407 | 0 | sentence-transformers | [
"sentence-transformers",
"onnx",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"code-search",
"code-embeddings",
"code",
"dataset:sentence-transformers/codesearchnet",
"base_model:sentence-transformers/all-MiniLM-L6-v2",
"base_model:quantized:sentence-transformers/all-Min... | sentence-similarity | 2026-01-04T16:12:52Z | # all-MiniLM-L6-v2-code-search-512
**Version:** v1.0
**Release Date:** 2026-01-04
**Base Model:** https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
---
## Overview
- `all-MiniLM-L6-v2-code-search-512` is a lightweight, high-accuracy [sentence-transformers](https://www.SBERT.net) fine-tuned specifica... | [] |
ymachida36/qwen3-4b-structured-output-lora-sft | ymachida36 | 2026-02-07T13:26:23Z | 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 | 2026-02-07T13:26:02Z | qwen3-4b-structured-output-lora
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **s... | [
{
"start": 133,
"end": 138,
"text": "QLoRA",
"label": "training method",
"score": 0.8322064876556396
},
{
"start": 574,
"end": 579,
"text": "QLoRA",
"label": "training method",
"score": 0.7354162931442261
}
] |
ApocalypseParty/G4-26B-ConfigB | ApocalypseParty | 2026-04-15T21:35:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"mergekit",
"merge",
"arxiv:2203.05482",
"base_model:ApocalypseParty/G4-26B-SFT-6",
"base_model:merge:ApocalypseParty/G4-26B-SFT-6",
"base_model:google/gemma-4-26B-A4B-it",
"base_model:merge:google/gemma-4-26B-A4B-it",
"endpoints_c... | image-text-to-text | 2026-04-15T21:32:02Z | # configB
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Linear](https://arxiv.org/abs/2203.05482) merge method.
### Models Merged
The following models were included in the merge:
* [goog... | [] |
travistest/mistral-grpo-stage1 | travistest | 2025-12-15T18:51:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"hf_jobs",
"unsloth",
"grpo",
"arxiv:2402.03300",
"base_model:unsloth/mistral-7b-instruct-v0.3-bnb-4bit",
"base_model:finetune:unsloth/mistral-7b-instruct-v0.3-bnb-4bit",
"endpoints_compatible",
"region:us"
] | null | 2025-12-15T18:06:37Z | # Model Card for mistral-grpo-stage1
This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.3-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-instruct-v0.3-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
qu... | [] |
Vinuit/SentinelAI-Filter-ONNX | Vinuit | 2026-03-10T17:44:02Z | 0 | 0 | peft | [
"peft",
"onnx",
"safetensors",
"mental-health",
"burnout-detection",
"lora",
"dual-head-classifier",
"workplace-wellbeing",
"base_model:google-bert/bert-base-uncased",
"base_model:adapter:google-bert/bert-base-uncased",
"region:us"
] | null | 2026-02-24T19:45:18Z | # SentinelAI BERT Filter - LoRA Adapters
LoRA fine-tuned BERT model for employee mental health classification in workplace messages. Part of the SentinelAI system for automated burnout detection via Slack message analysis.
## Model Description
- **Base Model:** bert-base-uncased (110M parameters)
- **Fine-tun... | [] |
sohambose98/sre-sft-lora | sohambose98 | 2026-04-25T22:27:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"hf_jobs",
"trl",
"base_model:Qwen/Qwen2.5-7B",
"base_model:finetune:Qwen/Qwen2.5-7B",
"endpoints_compatible",
"region:us"
] | null | 2026-04-25T22:05:56Z | # Model Card for sre-sft-lora
This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to t... | [] |
cyankiwi/Ovis2.6-30B-A3B-AWQ-4bit | cyankiwi | 2026-02-20T09:13:03Z | 72 | 0 | null | [
"safetensors",
"ovis2_6_moe",
"image-text-to-text",
"conversational",
"custom_code",
"arxiv:2508.11737",
"arxiv:2405.20797",
"base_model:AIDC-AI/Ovis2.6-30B-A3B",
"base_model:quantized:AIDC-AI/Ovis2.6-30B-A3B",
"license:apache-2.0",
"compressed-tensors",
"region:us"
] | image-text-to-text | 2026-02-20T09:11:59Z | # Ovis2.6-30B-A3B
<div align="center">
<img src=https://cdn-uploads.huggingface.co/production/uploads/637aebed7ce76c3b834cea37/3IK823BZ8w-mz_QfeYkDn.png width="30%"/>
</div>
## Introduction
We introduce **Ovis2.6-30B-A3B**, the latest advancement in the Ovis series of Multimodal Large Language Models (MLLMs). Buil... | [] |
AnonymousCS/populism_classifier_bsample_335 | AnonymousCS | 2025-08-28T01:37:36Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_english_bert_large_cased",
"base_model:finetune:AnonymousCS/populism_english_bert_large_cased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"reg... | text-classification | 2025-08-28T01:36:27Z | <!-- 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_335
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_cased](https://hug... | [] |
OwenZou/outputs | OwenZou | 2025-12-20T23:07:12Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:mistralai/Mixtral-8x7B-Instruct-v0.1",
"base_model:finetune:mistralai/Mixtral-8x7B-Instruct-v0.1",
"endpoints_compatible",
"region:us"
] | null | 2025-10-29T05:33:00Z | # Model Card for outputs
This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a... | [] |
Muapi/retro-anime-and-comic-style-vibrant-colors | Muapi | 2025-08-16T16:19:58Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-16T16:19:44Z | # Retro Anime and Comic style - Vibrant Colors
**Base model**: Flux.1 D
**Trained words**: CAICO
## 🧠 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"... | [] |
ooeoeo/opus-mt-en-de-ct2-float16 | ooeoeo | 2026-04-16T19:37:41Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"base",
"license:apache-2.0",
"region:us"
] | translation | 2026-04-16T19:37:37Z | # ooeoeo/opus-mt-en-de-ct2-float16
CTranslate2 float16 quantized version of `Helsinki-NLP/opus-mt-en-de`.
Converted for use in the [ooeoeo](https://ooeoeo.com) desktop engine
with the `opus-mt-server` inference runtime.
## Source
- Upstream model: [Helsinki-NLP/opus-mt-en-de](https://huggingface.co/Helsinki-NLP/opu... | [] |
WindyWord/translate-tc-big-et-en | WindyWord | 2026-04-20T13:35:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"estonian",
"english",
"et",
"en",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-20T12:46:22Z | # WindyWord.ai Translation — Estonian → English
**Translates Estonian → English.**
**Quality Rating: ⭐⭐½ (2.5★ Basic)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 2.5★ ⭐⭐½
- **Tier:** Basic
- **Composite sc... | [] |
hereticness/Heretic-Qwen3-Zero-Coder-Reasoning-V2-0.8B | hereticness | 2026-01-11T12:16:44Z | 4 | 1 | null | [
"safetensors",
"qwen3",
"heretic",
"text-generation",
"conversational",
"base_model:DavidAU/Qwen3-Zero-Coder-Reasoning-V2-0.8B",
"base_model:finetune:DavidAU/Qwen3-Zero-Coder-Reasoning-V2-0.8B",
"region:us"
] | text-generation | 2026-01-11T12:16:06Z | <div style="background: #000; margin: auto; border: 1px solid #FFFFFF; background-image: url('https://c.tenor.com/r47ZgZUPwEwAAAAC/tenor.gif'); background-size: 30vw 70vh; background-repeat: repeat;">
<style>
*::selection {background: transparent !important; color: inherit !important;}
p,a,summary,details{color:#cccccc... | [] |
YellowLabsStudio/goodglinda-7b-verifier | YellowLabsStudio | 2026-03-10T03:56:53Z | 12 | 0 | null | [
"qwen2",
"verification",
"multi-agent",
"edge-ai",
"security",
"qwen",
"7b",
"hmav",
"early-exit",
"custom_code",
"en",
"dataset:YellowLabsStudio/goodglinda-training-data",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"reg... | null | 2026-03-03T05:17:38Z | # GoodGlinda-7B-Verifier
[](https://huggingface.co/YellowLabsStudio/goodglinda-7b-verifier)
[](https://huggingface.co/datasets/YellowLabsStudio/goodglinda-training-dat... | [] |
pretentiousApple/Hercule_LoRA | pretentiousApple | 2025-08-10T15:42:03Z | 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 | 2025-08-10T15:39:11Z | <!-- 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 - pretentiousApple/Hercule_LoRA
<Gallery />
## Model description
These are pretentiousApple/Hercu... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7492849230766296
},
{
"start": 328,
"end": 332,
"text": "LoRA",
"label": "training method",
"score": 0.7897496819496155
},
{
"start": 475,
"end": 479,
"text": "LoRA",
"l... |
buelfhood/conplag1_codet5_ep30_bs16_lr2e-05_l512_s42_ppy_loss | buelfhood | 2025-11-16T22:04:38Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text-classification",
"generated_from_trainer",
"base_model:Salesforce/codet5-small",
"base_model:finetune:Salesforce/codet5-small",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-16T22:04:30Z | <!-- 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. -->
# conplag1_codet5_ep30_bs16_lr2e-05_l512_s42_ppy_loss
This model is a fine-tuned version of [Salesforce/codet5-small](https://huggi... | [] |
haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all | haryoaw | 2024-07-27T18:24:24Z | 0 | 1 | transformers | [
"transformers",
"pytorch",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"dataset:tweet_sentiment_multilingual",
"base_model:microsoft/mdeberta-v3-base",
"base_model:finetune:microsoft/mdeberta-v3-base",
"license:mit",
"model-index",
"text-embeddings-inference",
"endpoints_com... | text-classification | 2024-07-27T18:23:50Z | <!-- 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. -->
# scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all
This model is a fine-tuned version of [microsoft/mdeberta-v3-base](... | [] |
The-frizzy1/Qwen-Image-Edit-2509-GGUF | The-frizzy1 | 2026-03-24T17:34:13Z | 0 | 0 | null | [
"comfyui",
"workflow",
"qwen",
"gguf",
"low-vram",
"text-to-image",
"image-to-image",
"beginner-friendly",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-03-24T17:34:09Z | # Qwen Image & Edit 2509 GGUF — Beginner Friendly
**By:** [The_frizzy1](https://civitai.com/user/The_frizzy1)
**Hardware target:** 4 GB VRAM (Q4_K_S) / 12 GB VRAM (Q8)
**CivitAI:** https://civitai.com/models/2229874/qwen-image-and-edit-2509-gguf-beginner-friendly
**YouTube:** https://www.youtube.com/@the_frizzy1
🎥 *... | [] |
ShionYe/Qwen2.5-7B-Instruct-GRPO | ShionYe | 2026-04-26T15:38:48Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"grpo",
"dataset:AI-MO/NuminaMath-TIR",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-04-26T15:38:16Z | # Model Card for Qwen2.5-7B-Instruct-GRPO
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the [AI-MO/NuminaMath-TIR](https://huggingface.co/datasets/AI-MO/NuminaMath-TIR) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
... | [
{
"start": 1059,
"end": 1063,
"text": "GRPO",
"label": "training method",
"score": 0.7417297959327698
},
{
"start": 1358,
"end": 1362,
"text": "GRPO",
"label": "training method",
"score": 0.8394742608070374
}
] |
olivialong/cat_half | olivialong | 2025-11-28T21:57:10Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-11-28T19:55:36Z | # Model Card for cat_half
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 import pipeline
question = "If you had a time machine, but coul... | [] |
rbelanec/train_rte_42_1774791064 | rbelanec | 2026-03-29T13:33:33Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Llama-3.2-1B-Instruct",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"license:llama3.2",
"region:us"
] | text-generation | 2026-03-29T13:31:46Z | <!-- 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. -->
# train_rte_42_1774791064
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llam... | [] |
snowytsai/Wan2.2-I2V-A14B | snowytsai | 2026-03-27T06:46:03Z | 0 | 0 | wan2.2 | [
"wan2.2",
"diffusers",
"safetensors",
"image-to-video",
"en",
"zh",
"arxiv:2503.20314",
"license:apache-2.0",
"region:us"
] | image-to-video | 2026-03-27T06:46:03Z | # Wan2.2
<p align="center">
<img src="assets/logo.png" width="400"/>
<p>
<p align="center">
💜 <a href="https://wan.video"><b>Wan</b></a>    ｜    🖥️ <a href="https://github.com/Wan-Video/Wan2.2">GitHub</a>    |   🤗 <a href="https://huggingface.co/Wan-AI/">Hugging Face</a>&nb... | [] |
DevQuasar/ibm-granite.granite-4.0-h-1b-GGUF | DevQuasar | 2025-10-29T04:20:01Z | 41 | 0 | null | [
"gguf",
"text-generation",
"base_model:ibm-granite/granite-4.0-h-1b",
"base_model:quantized:ibm-granite/granite-4.0-h-1b",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-10-29T04:10:10Z | [<img src="https://raw.githubusercontent.com/csabakecskemeti/devquasar/main/dq_logo_black-transparent.png" width="200"/>](https://devquasar.com)
Quantized version of: [ibm-granite/granite-4.0-h-1b](https://huggingface.co/ibm-granite/granite-4.0-h-1b)
'Make knowledge free for everyone'
<p align="center">
Made with ... | [] |
OkoInosa/corgy_dog_LoRA | OkoInosa | 2025-09-24T16:19:26Z | 0 | 0 | diffusers | [
"diffusers",
"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++",
"region:us"
] | text-to-image | 2025-09-24T16:01:27Z | <!-- 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 - OkoInosa/corgy_dog_LoRA
<Gallery />
## Model description
These are OkoInosa/corgy_dog_LoRA LoRA... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7474061846733093
},
{
"start": 316,
"end": 320,
"text": "LoRA",
"label": "training method",
"score": 0.7947419881820679
},
{
"start": 463,
"end": 467,
"text": "LoRA",
"l... |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-256D-3L-4H-1024I | arithmetic-circuit-overloading | 2026-02-27T01:26:09Z | 184 | 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 | 2026-02-27T01:13:00Z | <!-- 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-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-256D-3L-4H-1024I
This model is a fine-tuned version of [me... | [] |
IsaacMwesigwa/credit-score-autoencoder-weights | IsaacMwesigwa | 2026-04-07T21:02:23Z | 0 | 0 | pytorch | [
"pytorch",
"credit-risk",
"tabular",
"finance",
"other",
"en",
"license:mit",
"region:us"
] | other | 2026-04-07T20:59:53Z | # Credit Score Autoencoder Weights
## Model Summary
This repository stores a model artifact used by the credit-score predictor project.
The artifact is published as-is for reproducibility and deployment.
## Files
- `autoencoder_weights.pt`: uploaded model artifact
- `README.md`: autogenerated model card
## Intende... | [] |
godninja/Affine-crown_v14-5Dr2bBgVtFJYvJi5mqVeWWrz8kfC2wwyCWYDYBATjJ4ZiKuL | godninja | 2026-02-20T05:55:51Z | 10 | 0 | transformers | [
"transformers",
"safetensors",
"exaone_moe",
"text-generation",
"lg-ai",
"exaone",
"k-exaone",
"conversational",
"en",
"ko",
"es",
"de",
"ja",
"vi",
"arxiv:2601.01739",
"license:other",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-10T15:57:27Z | <br>
<br>
<p align="center">
<img src="assets/K-EXAONE_logo_gray.png" width="400">
<br>
<br>
<br>
<div align="center">
<a href="https://huggingface.co/collections/LGAI-EXAONE/k-exaone" style="text-decoration: none;">
<img src="https://img.shields.io/badge/🤗-HuggingFace-FC926C?style=for-the-badge" alt="HuggingFa... | [] |
Muapi/white-turtleneck | Muapi | 2025-09-03T01:49:34Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-03T01:49:13Z | # White turtleneck
**Base model**: Flux.1 D
**Trained words**: turtl3n3ck, white turtleneck top
## 🧠 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"
... | [] |
zkarbie/context-lattice-semantic-reranker | zkarbie | 2026-04-06T02:56:28Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"cross-encoder",
"reranker",
"generated_from_trainer",
"dataset_size:1600",
"loss:BinaryCrossEntropyLoss",
"text-ranking",
"arxiv:1908.10084",
"base_model:cross-encoder/ms-marco-MiniLM-L6-v2",
"base_model:finetune:cross-encoder/ms-marco-MiniLM-L6... | text-ranking | 2026-04-06T02:56:22Z | # CrossEncoder based on cross-encoder/ms-marco-MiniLM-L6-v2
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) using the [sentence-transformers](https://www.SBERT.net... | [] |
mradermacher/RimTalk-Mini-v1-i1-GGUF | mradermacher | 2025-12-28T20:08:15Z | 42 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:TheDrummer/RimDialogue-3B-v1",
"base_model:quantized:TheDrummer/RimDialogue-3B-v1",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-09-06T06:10:27Z | ## 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... | [] |
Tanayuya/qwen3-4b-structured-output-lora-ver32 | Tanayuya | 2026-02-08T07:42:26Z | 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 | 2026-02-08T07:42:22Z | qwen3-4b-structured-output-lora-ver32
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": 0.7981715798377991
}
] |
shaohuay/Qwen3-VL-4B-Instruct-trl-sft | shaohuay | 2025-10-15T21:21:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen3-VL-4B-Instruct",
"base_model:finetune:Qwen/Qwen3-VL-4B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-10-15T20:35:54Z | # Model Card for Qwen3-VL-4B-Instruct-trl-sft
This model is a fine-tuned version of [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a ... | [] |
luckeciano/Qwen-2.5-7B-DrGRPO-Base-Adam-2Iterations-0.002-v3_3220 | luckeciano | 2025-09-19T21:33:10Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"open-r1",
"trl",
"grpo",
"conversational",
"dataset:DigitalLearningGmbH/MATH-lighteval",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"text-generation... | text-generation | 2025-09-19T18:12:15Z | # Model Card for Qwen-2.5-7B-DrGRPO-Base-Adam-2Iterations-0.002-v3_3220
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B) on the [DigitalLearningGmbH/MATH-lighteval](https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval) dataset.
It has been trained ... | [] |
alex-white-ai/EliseCarter-Wan2.2 | alex-white-ai | 2026-02-19T14:07:43Z | 0 | 0 | null | [
"feature",
"training",
"new",
"wavespeed",
"license:other",
"region:us"
] | null | 2026-02-19T14:07:23Z | # wavespeed-ai/wan-2.2-image-lora-trainer
<Gallery />
## Model description
## Trigger words
You should use `EliseCarter` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/alex-white-ai/EliseCarter-Wan2.2/tree/main) them in the Files & ver... | [] |
mradermacher/Llama-3.1-8B-sft-SPIN-Llama-3.1-70B-Instruct-IPO-GGUF | mradermacher | 2025-09-02T21:10:32Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"trl",
"dpo",
"en",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-02T19:36:22Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
grupo4-bisite/FL-CodeLlama-7b-Instruct-vera-5-Q4_0-GGUF | grupo4-bisite | 2026-01-30T09:53:01Z | 3 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:grupo4-bisite/FL-CodeLlama-7b-Instruct-vera-5",
"base_model:quantized:grupo4-bisite/FL-CodeLlama-7b-Instruct-vera-5",
"endpoints_compatible",
"region:us"
] | null | 2026-01-30T09:52:44Z | # grupo4-bisite/FL-CodeLlama-7b-Instruct-vera-5-Q4_0-GGUF
This model was converted to GGUF format from [`grupo4-bisite/FL-CodeLlama-7b-Instruct-vera-5`](https://huggingface.co/grupo4-bisite/FL-CodeLlama-7b-Instruct-vera-5) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-r... | [] |
xummer/llama3-1-8b-squad_translate-lora-th | xummer | 2026-03-16T01:00:58Z | 27 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3.1-8B-Instruct",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:adapter:meta-llama/Llama-3.1-8B-Instruct",
"license:other",
"region:us"
] | text-generation | 2026-03-13T18:42:59Z | <!-- 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. -->
# th
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1... | [] |
burtenshaw/lora-no-regret-grpo | burtenshaw | 2025-10-01T11:31:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"hf_jobs",
"grpo",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-0.5B-Instruct",
"text-generation-inference",
"endpoints_compatible... | text-generation | 2025-10-01T09:01:46Z | # Model Card for lora-no-regret-grpo
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-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 ma... | [] |
WindyWord/translate-fi-xh | WindyWord | 2026-04-20T13:27:46Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"finnish",
"xhosa",
"fi",
"xh",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-17T03:10:52Z | # WindyWord.ai Translation — Finnish → Xhosa
**Translates Finnish → Xhosa.**
**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
- **Composite ... | [] |
EricSong1216/act_so101_pick_place_v1 | EricSong1216 | 2026-03-16T15:10:42Z | 30 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:EricSong1216/so101-pick-place-official-v1",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-16T15:10:24Z | # 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":... |
dina1/bert-imdb-sentiment | dina1 | 2025-08-07T09:58:20Z | 0 | 0 | null | [
"safetensors",
"bert",
"sentiment",
"imdb",
"text-classification",
"en",
"dataset:imdb",
"license:apache-2.0",
"model-index",
"region:us"
] | text-classification | 2025-08-07T09:34:27Z | # BERT IMDB Sentiment Classifier
This model is a fine-tuned version of `bert-base-uncased` on the IMDB movie reviews dataset.
## Task
Binary Sentiment Classification:
- `0` → Negative
- `1` → Positive
## Usage
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
model = AutoModelFo... | [] |
sujalappa/speaker-segmentation-fine-tuned | sujalappa | 2025-09-22T17:19:51Z | 8 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"pyannet",
"speaker-diarization",
"speaker-segmentation",
"generated_from_trainer",
"dataset:sujalappa/temp-speaker-diarization-synthetic-dataset",
"base_model:pyannote/speaker-diarization-3.1",
"base_model:finetune:pyannote/speaker-diarization-3.1",
... | null | 2025-09-22T16:23:01Z | <!-- 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. -->
# speaker-diarization-fine-tuned
This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/py... | [] |
FriendliAI/MiniCPM-o-2_6 | FriendliAI | 2025-12-24T02:18:10Z | 7 | 0 | transformers | [
"transformers",
"safetensors",
"minicpmo",
"feature-extraction",
"minicpm-o",
"omni",
"vision",
"ocr",
"multi-image",
"video",
"custom_code",
"audio",
"speech",
"voice cloning",
"live Streaming",
"realtime speech conversation",
"asr",
"tts",
"any-to-any",
"multilingual",
"dat... | any-to-any | 2025-12-24T02:18:08Z | <h1>A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone</h1>
[GitHub](https://github.com/OpenBMB/MiniCPM-o) | [Online Demo](https://minicpm-omni-webdemo-us.modelbest.cn) | [Technical Blog](https://openbmb.notion.site/MiniCPM-o-2-6-A-GPT-4o-Level-MLLM-for-Vision-Speech-and-Multimodal-Live... | [] |
ikedabent/llm_ad_qwen2.5-7b-multi003 | ikedabent | 2026-02-27T17:26:53Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/dbbench_sft_dataset_react_v4",
"base_model:unsloth/Qwen2.5-7B-Instruct",
"base_model:adapter:unsloth/Qwen2.5-7B-Instruct",
"license:apache-2.0",... | text-generation | 2026-02-27T17:23:57Z | # unsloth/Qwen2.5-7B-Instruct
This repository provides a **LoRA adapter** fine-tuned from
**unsloth/Qwen2.5-7B-Instruct** 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 ... | [
{
"start": 2,
"end": 9,
"text": "unsloth",
"label": "training method",
"score": 0.7513039708137512
},
{
"start": 60,
"end": 64,
"text": "LoRA",
"label": "training method",
"score": 0.8795894980430603
},
{
"start": 93,
"end": 100,
"text": "unsloth",
"la... |
VAST-AI/AniGen | VAST-AI | 2026-04-13T16:33:39Z | 0 | 2 | null | [
"animatable",
"rigging",
"3D",
"Tripo",
"VAST",
"image-to-3d",
"en",
"arxiv:2604.08746",
"base_model:microsoft/TRELLIS-image-large",
"base_model:finetune:microsoft/TRELLIS-image-large",
"license:mit",
"region:us"
] | image-to-3d | 2026-03-03T21:09:14Z | # AniGen_Weights
Pretrained checkpoints for [AniGen](https://github.com/VAST-AI-Research/AniGen), a unified framework for generating animatable 3D assets from a single image.
<p align="center">
<a href="https://arxiv.org/pdf/2604.08746"><img src="https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv&logoColor=whi... | [] |
nahiar/whisper-v1 | nahiar | 2026-03-30T09:40:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"en",
"zh",
"de",
"es",
"ru",
"ko",
"fr",
"ja",
"pt",
"tr",
"pl",
"ca",
"nl",
"ar",
"sv",
"it",
"id",
"hi",
"fi",
"vi",
"he",
"uk",
"el",
"ms",
"cs",
"ro",
"da",
"hu",
... | automatic-speech-recognition | 2026-03-30T09:36:34Z | # Whisper
Whisper is a state-of-the-art model for automatic speech recognition (ASR) and speech translation, proposed in the paper
[Robust Speech Recognition via Large-Scale Weak Supervision](https://huggingface.co/papers/2212.04356) by Alec Radford
et al. from OpenAI. Trained on >5M hours of labeled data, Whisper d... | [] |
contemmcm/d54424a6456fb2d42d7c2b450684a002 | contemmcm | 2025-11-10T14:53:50Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:google-bert/bert-large-cased-whole-word-masking-finetuned-squad",
"base_model:finetune:google-bert/bert-large-cased-whole-word-masking-finetuned-squad",
"license:apache-2.0",
"text-embeddings-inferenc... | text-classification | 2025-11-10T13:48:27Z | <!-- 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. -->
# d54424a6456fb2d42d7c2b450684a002
This model is a fine-tuned version of [google-bert/bert-large-cased-whole-word-masking-finetuned... | [
{
"start": 589,
"end": 597,
"text": "F1 Macro",
"label": "training method",
"score": 0.7596058249473572
},
{
"start": 1413,
"end": 1421,
"text": "F1 Macro",
"label": "training method",
"score": 0.7291315793991089
}
] |
mlx-community/YOLO26s-OptiQ-6bit | mlx-community | 2026-04-11T01:01:28Z | 0 | 0 | mlx | [
"mlx",
"quantized",
"mixed-precision",
"yolo",
"yolo26",
"object-detection",
"optiq",
"apple-silicon",
"base_model:Ultralytics/YOLO26",
"base_model:finetune:Ultralytics/YOLO26",
"license:agpl-3.0",
"region:us"
] | object-detection | 2026-04-11T00:49:58Z | # YOLO26s-OptiQ-6bit
> Mixed-precision quantized YOLO26s for Apple Silicon via OptiQ
This is a mixed-precision quantized version of [YOLO26s](https://github.com/ultralytics/ultralytics) in MLX format, optimized with [mlx-optiq](https://pypi.org/project/mlx-optiq/) for Apple Silicon inference via [yolo-mlx](https://py... | [] |
simaai/LFM2-350M-a16w4 | simaai | 2026-05-04T09:16:22Z | 0 | 0 | llima | [
"llima",
"llm",
"generative_ai",
"embedded",
"sima",
"liquidai",
"lfm2",
"text-generation",
"base_model:LiquidAI/LFM2-350M",
"base_model:finetune:LiquidAI/LFM2-350M",
"license:mit",
"region:us"
] | text-generation | 2026-04-24T16:19:05Z | # LFM2-350M-a16w4: Optimized for SiMa.ai Modalix
## Overview
This repository contains the **LFM2-350M-a16w4** model, optimized and compiled for the **SiMa.ai Modalix** platform.
- **Model Architecture:** LFM2 (350M parameters)
- **Quantization:** Hybrid
- **Prompt Processing:** A16W8 (16-bit activations, 8-bit wei... | [] |
PRadecki/convnextv2-nano-k5-in1k-128 | PRadecki | 2026-01-02T00:18:20Z | 0 | 0 | timm | [
"timm",
"safetensors",
"image-classification",
"license:apache-2.0",
"region:us"
] | image-classification | 2025-12-31T09:43:05Z | # Model card for convnextv2-nano-k5-in1k-128
ConvNeXtV2-Nano (k=5) trained from scratch on ImageNet-1K @ 128x128.
## Training Recipe:
- ConvNeXt-V2 (Woo et al., 2023) Table 9, IN-1K Nano end-to-end.
- BF16 AMP
## Model Details
- **Model:** convnextv2_nano
- **Model Kwargs:**
- kernel_sizes: 5
- **Input Size:**
... | [] |
AlignmentResearch/obfuscation-atlas-gemma-3-27b-it-kl1-det10-seed3-diverse_deception_probe | AlignmentResearch | 2026-02-20T21:59:38Z | 1 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"model-type:honest",
"arxiv:2602.15515",
"base_model:google/gemma-3-27b-it",
"base_model:adapter:google/gemma-3-27b-it",
"license:mit",
"region:us"
] | null | 2026-02-17T10:12:06Z | # RLVR-trained policy from The Obfuscation Atlas
This is a policy trained on MBPP-Honeypot with deception probes,
from the [Obfuscation Atlas paper](https://arxiv.org/abs/2602.15515),
uploaded for reproducibility and further research.
The training code and RL environment are available at: https://github.com/Alignment... | [] |
RahulKadam0909/neutts-air-hi-preview-Q4_K_M-GGUF | RahulKadam0909 | 2026-02-11T06:21:46Z | 30 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-to-speech",
"hi",
"en",
"base_model:jaeyong2/neutts-air-hi-preview",
"base_model:quantized:jaeyong2/neutts-air-hi-preview",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-to-speech | 2026-02-11T06:21:39Z | # RahulKadam0909/neutts-air-hi-preview-Q4_K_M-GGUF
This model was converted to GGUF format from [`jaeyong2/neutts-air-hi-preview`](https://huggingface.co/jaeyong2/neutts-air-hi-preview) 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 mo... | [] |
Synthyra/FastESMFold | Synthyra | 2026-03-26T20:52:22Z | 253 | 0 | transformers | [
"transformers",
"safetensors",
"fast_esmfold",
"feature-extraction",
"protein",
"structure-prediction",
"esmfold",
"test-time-training",
"custom_code",
"arxiv:2411.02109",
"arxiv:2412.05496",
"region:us"
] | feature-extraction | 2026-03-23T15:01:47Z | # NOTE
The GitHub with the implementation and requirements.txt can be found [here](https://github.com/Synthyra/FastPLMs.git)
# FastESMFold
FastESMFold is a self-contained, HuggingFace-compatible reimplementation of ESMFold with optional **Test-Time Training (TTT)** and multi-backend attention (SDPA, Flash, Flex)... | [
{
"start": 146,
"end": 157,
"text": "FastESMFold",
"label": "training method",
"score": 0.7014818787574768
},
{
"start": 1514,
"end": 1521,
"text": "ESMFold",
"label": "training method",
"score": 0.7192486524581909
},
{
"start": 1778,
"end": 1785,
"text": ... |
Panda512/smolvla-0406-v1 | Panda512 | 2026-04-07T01:40:04Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Panda512/record-0406-v1",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-07T01:39:34Z | # 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... | [] |
simon-pltk/codi-gpt2-prontoqa-latent | simon-pltk | 2026-03-19T15:23:14Z | 0 | 0 | pytorch | [
"pytorch",
"gpt2",
"prontoqa",
"latent-reasoning",
"chain-of-thought",
"distillation",
"codi",
"license:mit",
"region:us"
] | null | 2026-03-19T15:23:03Z | # CODI — GPT-2 ProntoQA (Latent Reasoning)
A **CODI** (Chain-of-thought Distillation) model trained on ProntoQA for latent
chain-of-thought reasoning. The model wraps GPT-2 with LoRA adapters and a
distillation objective that compresses explicit chain-of-thought steps into
latent embeddings.
## Quick Start
```bash
p... | [] |
safe-autonomous-systems/sac-CylinderJet2D-medium-v0 | safe-autonomous-systems | 2026-02-04T08:43:29Z | 36 | 0 | stable-baselines3 | [
"stable-baselines3",
"reinforcement-learning",
"deep-reinforcement-learning",
"fluidgym",
"active-flow-control",
"fluid-dynamics",
"simulation",
"CylinderJet2D-medium-v0",
"arxiv:2601.15015",
"model-index",
"region:us"
] | reinforcement-learning | 2026-01-27T09:02:37Z | # SAC on CylinderJet2D-medium-v0 (FluidGym)
This repository is part of the **FluidGym** benchmark results. It contains trained Stable Baselines3 agents for the specialized **CylinderJet2D-medium-v0** environment.
## Evaluation Results
### Global Performance (Aggregated across 5 seeds)
**Mean Reward:** 0.38 ± 0.17
#... | [] |
alexanderyj/gemma-3-4b-it_fine_tuning_base-tr_echt_90000_2026-04-20 | alexanderyj | 2026-04-19T23:41:26Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/gemma-3-4b-it",
"base_model:finetune:google/gemma-3-4b-it",
"endpoints_compatible",
"region:us"
] | null | 2026-04-19T23:40:11Z | # Model Card for gemma-3-4b-it_fine_tuning_base-tr_echt_90000_2026-04-20
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... | [] |
huskyhong/wzryyykl-mc-wsfj | huskyhong | 2026-01-14T20:31:22Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-14T20:25:29Z | # 王者荣耀语音克隆-马超-无双飞将
基于 VoxCPM 的王者荣耀英雄及皮肤语音克隆模型系列，支持多种英雄和皮肤的语音风格克隆与生成。
## 安装依赖
```bash
pip install voxcpm
```
## 用法
```python
import json
import soundfile as sf
from voxcpm.core import VoxCPM
from voxcpm.model.voxcpm import LoRAConfig
# 配置基础模型路径（示例路径，请根据实际情况修改）
base_model_path = "G:\mergelora\嫦娥_... | [] |
FreedomIntelligence/HuatuoGPT-o1-7B | FreedomIntelligence | 2025-01-06T02:40:16Z | 233 | 57 | null | [
"safetensors",
"medical",
"text-generation",
"en",
"zh",
"dataset:FreedomIntelligence/medical-o1-reasoning-SFT",
"dataset:FreedomIntelligence/medical-o1-verifiable-problem",
"arxiv:2412.18925",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:apache... | text-generation | 2024-12-26T04:28:55Z | <div align="center">
<h1>
HuatuoGPT-o1-7B
</h1>
</div>
<div align="center">
<a href="https://github.com/FreedomIntelligence/HuatuoGPT-o1" target="_blank">GitHub</a> | <a href="https://arxiv.org/pdf/2412.18925" target="_blank">Paper</a>
</div>
# <span>Introduction</span>
**HuatuoGPT-o1** is a medical LLM designed fo... | [] |
McGill-NLP/LLM2Vec-Gen-Llama31-8B | McGill-NLP | 2026-04-04T14:41:28Z | 6 | 0 | transformers | [
"transformers",
"safetensors",
"text-embedding",
"embeddings",
"information-retrieval",
"beir",
"text-classification",
"language-model",
"text-clustering",
"text-semantic-similarity",
"text-evaluation",
"text-reranking",
"feature-extraction",
"sentence-similarity",
"Sentence Similarity",... | sentence-similarity | 2026-03-03T19:20:23Z | # LLM2Vec-Gen: Generative Embeddings from Large Language Models
> LLM2Vec-Gen is a recipe to train interpretable, generative embeddings that encode the potential answer of an LLM to a query rather than the query itself.
- **Repository**: https://github.com/McGill-NLP/llm2vec-gen
- **Paper**: https://arxiv.org/abs/2603... | [] |
genbio-ai/genbio-pathfm | genbio-ai | 2026-04-07T22:39:54Z | 1 | 9 | null | [
"safetensors",
"genbio_pathfm",
"biology",
"histopathology",
"foundation-model",
"pathology",
"jepa",
"dino",
"custom_code",
"en",
"license:other",
"region:us"
] | null | 2026-03-15T06:24:40Z | # GenBio-PathFM
GenBio-PathFM is a histopathology foundation (FM) model from [GenBio AI](https://genbio.ai/).
At the time of release, GenBio-PathFM is the strongest open-weight histopathology FM and the only state-of-the-art histopathology F... | [] |
ferrazzipietro/ULS-MultiClinNERnl-Mistral-7B-v0.1-disease | ferrazzipietro | 2026-03-15T20:37:11Z | 93 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:mistralai/Mistral-7B-v0.1",
"lora",
"transformers",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | null | 2026-03-15T20:15:46Z | <!-- 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. -->
# ULS-MultiClinNERnl-Mistral-7B-v0.1-disease
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.... | [] |
udbhav89/domain-specific-modern-bert-spam-classifier | udbhav89 | 2026-01-16T18:52:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"text-classification",
"spam-detection",
"en",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-01-16T18:42:15Z | # Domain-Specific ModernBERT Spam Classifier
Fine-tuned ModernBERT model for spam classification with domain-specific prefixes.
## Usage
This model expects text with a domain prefix:
- `[crypto]` for crypto/blockchain related content
- `[rideshare]` for rideshare/transportation related content
Example:
```python
fr... | [] |
ferrazzipietro/tlocvsdyspneaTask-unsup-Qwen3-8B-datav3 | ferrazzipietro | 2026-04-08T12:14:26Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:ferrazzipietro/unsup-Qwen3-8B-datav3",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:ferrazzipietro/unsup-Qwen3-8B-datav3",
"region:us"
] | text-generation | 2026-04-08T09:16:27Z | <!-- 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. -->
# tlocvsdyspneaTask-unsup-Qwen3-8B-datav3
This model is a fine-tuned version of [ferrazzipietro/unsup-Qwen3-8B-datav3](https://hugg... | [
{
"start": 485,
"end": 493,
"text": "F1 Macro",
"label": "training method",
"score": 0.7857574224472046
},
{
"start": 504,
"end": 515,
"text": "F1 Weighted",
"label": "training method",
"score": 0.8959201574325562
},
{
"start": 1269,
"end": 1277,
"text": "... |
contemmcm/6c9de378df77914dad19a82f5848d097 | contemmcm | 2025-11-18T20:44:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"luke",
"text-classification",
"generated_from_trainer",
"base_model:studio-ousia/luke-japanese-large-lite",
"base_model:finetune:studio-ousia/luke-japanese-large-lite",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-18T20:39:25Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 6c9de378df77914dad19a82f5848d097
This model is a fine-tuned version of [studio-ousia/luke-japanese-large-lite](https://huggingfac... | [] |
LLM-course/chess-feki-malek | LLM-course | 2026-01-25T13:46:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"chess_transformer",
"text-generation",
"chess",
"llm-course",
"chess-challenge",
"custom_code",
"license:mit",
"region:us"
] | text-generation | 2026-01-25T13:46:21Z | # chess-feki-malek
Chess model submitted to the LLM Course Chess Challenge.
## Submission Info
- **Submitted by**: [malekfeki14](https://huggingface.co/malekfeki14)
- **Parameters**: 923,340
- **Organization**: LLM-course
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = Auto... | [
{
"start": 2,
"end": 18,
"text": "chess-feki-malek",
"label": "training method",
"score": 0.7605827450752258
},
{
"start": 365,
"end": 381,
"text": "chess-feki-malek",
"label": "training method",
"score": 0.7505466938018799
}
] |
tshiamor/groot-n15-mcx-card | tshiamor | 2026-02-10T02:47:56Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"groot",
"robotics",
"dataset:tshiamor/mcx-card-pizero",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-08T21:05:52Z | # Model Card for groot
<!-- 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.... | [] |
ishanmakkar/visual-grounding-adapter | ishanmakkar | 2025-12-02T22:14:22Z | 1 | 0 | peft | [
"peft",
"safetensors",
"visual-grounding",
"qwen2-vl",
"multimodal",
"base_model:Qwen/Qwen2-VL-7B-Instruct",
"base_model:adapter:Qwen/Qwen2-VL-7B-Instruct",
"region:us"
] | null | 2025-11-24T18:52:45Z | # Visual Grounding Adapter
Fine-tuned adapter for Qwen2-VL-7B for visual grounding tasks.
## Usage
```python
from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
from peft import PeftModel
import torch
# Load base
model = Qwen2VLForConditionalGeneration.from_pretrained(
"Qwen/Qwen2-VL-7B-Inst... | [] |
mradermacher/Llama-3.3-70B-Instruct-heretic-v2-GGUF | mradermacher | 2025-12-06T23:30:55Z | 219 | 0 | transformers | [
"transformers",
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"de",
"base_model:TeeZee/Llama-3.3-70B-Instruct-heretic-v2",
"base_model:quantized:TeeZee/Llama-3.3-70B-I... | null | 2025-12-06T17:21:57Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
dureduck/1030_dp_lp_nailkit_3x4_grid_3_each | dureduck | 2025-10-31T15:43:53Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:dureduck/lift_place_graygreencontainer_3x4_grid_three_each",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-31T15:38:19Z | # 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 ... | [] |
mcnckc/dream-booth-2e6-1500 | mcnckc | 2026-02-07T07:47:43Z | 0 | 0 | diffusers | [
"diffusers",
"tensorboard",
"safetensors",
"text-to-image",
"dreambooth",
"diffusers-training",
"stable-diffusion",
"stable-diffusion-diffusers",
"base_model:stable-diffusion-v1-5/stable-diffusion-v1-5",
"base_model:finetune:stable-diffusion-v1-5/stable-diffusion-v1-5",
"license:creativeml-openr... | text-to-image | 2026-01-27T18:39:45Z | <!-- 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. -->
# DreamBooth - mcnckc/dream-booth-2e6-1500
This is a dreambooth model derived from stable-diffusion-v1-5/stable-diffusion-... | [
{
"start": 199,
"end": 209,
"text": "DreamBooth",
"label": "training method",
"score": 0.9576106667518616
},
{
"start": 251,
"end": 261,
"text": "dreambooth",
"label": "training method",
"score": 0.9533475637435913
},
{
"start": 380,
"end": 390,
"text": "D... |
bennethinz/distilbert-base-uncased-finetuned-spam-detection-dataset-splits | bennethinz | 2025-09-10T07:57:42Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"re... | text-classification | 2025-09-10T07:57:26Z | <!-- 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. -->
# distilbert-base-uncased-finetuned-spam-detection-dataset-splits
This model is a fine-tuned version of [distilbert-base-uncased](h... | [] |
cglez/bert-dapt-imdb-uncased | cglez | 2025-10-14T09:48:07Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:stanfordnlp/imdb",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-09-12T18:21:01Z | # Model Card: BERT-DAPT-IMDb
A domain-adapted BERT-base model, further pre-trained on the IMDb dataset text.
## Model Details
### Description
This model is based on the [BERT base (uncased)](https://huggingface.co/google-bert/bert-base-uncased)
architecture and was further pre-trained (domain-adapted) using the tex... | [] |
Raphael4287/Raphael | Raphael4287 | 2026-03-15T08:54:56Z | 0 | 3 | null | [
"region:us"
] | null | 2026-03-15T08:50:45Z | # Raphael: Multimodal AI Desktop Copilot
# 專案簡介 (Project Overview)
Raphael (拉菲爾) 是一款次世代的智慧桌面助理，旨在重塑人機協作體驗。透過整合語音感官、視覺辨識與大型語言模型 (LLM)，Raphael 能像真人助手一樣「看見」你的螢幕、「聽懂」你的需求，並直接在你的電腦上執行複雜任務。
Raphael is a next-generation AI desktop assistant designed to reshape the human-computer interaction experience. By integrating voice s... | [] |
irlab-udc/MetaHate-mBERT-PT | irlab-udc | 2025-11-27T12:28:31Z | 3 | 0 | null | [
"safetensors",
"bert",
"hate speech",
"text-classification",
"pt",
"dataset:irlab-udc/MetaHate-mBERT-PT",
"arxiv:2510.11167",
"license:apache-2.0",
"region:us"
] | text-classification | 2025-11-27T12:26:35Z | # MetaHate-mBERT-PT
## Model Description
This is a fine-tuned mBERT model specifically designed to detect hate speech in text in Portuguese. The model is based on the `bert-base-multilingual-cased` architecture and has been fine-tuned on a custom dataset for the task of binary text classification, where the labels ar... | [] |
microsoft/Dayhoff-170M-GRS-26000 | microsoft | 2026-02-24T01:51:15Z | 966 | 0 | transformers | [
"transformers",
"safetensors",
"jamba",
"text-generation",
"protein-generation",
"custom_code",
"dataset:microsoft/Dayhoff",
"arxiv:2502.12479",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-24T01:51:07Z | # Model Card for Dayhoff
Dayhoff is an Atlas of both protein sequence data and generative language models — a centralized resource that brings together 3.34 billion protein sequences across 1.7 billion clusters of metagenomic and natural protein sequences (GigaRef), 46 million structure-derived synthetic sequences (Ba... | [] |
Adanato/qwen25_3b_qwen25_qwen3_rank_only-qwen25_qwen3_rank_only_cluster_3 | Adanato | 2026-02-16T22:08:12Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-3B",
"base_model:finetune:Qwen/Qwen2.5-3B",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-16T22:04:49Z | <!-- 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. -->
# Qwen2.5-3B_e1_qwen25_qwen3_rank_only_cluster_3
This model is a fine-tuned version of [Qwen/Qwen2.5-3B](https://huggingface.co/Qwe... | [] |
jackf857/llama-3-8b-base-simpo-8xh200 | jackf857 | 2026-04-15T05:59:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"alignment-handbook",
"simpo",
"generated_from_trainer",
"conversational",
"dataset:HuggingFaceH4/ultrafeedback_binarized",
"base_model:W-61/llama-3-8b-base-sft-ultrachat-8xh200",
"base_model:finetune:W-61/llama-3-8b-base-sft-ultrachat-8... | text-generation | 2026-04-15T05:54:28Z | <!-- 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-3-8b-base-simpo-8xh200
This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingfac... | [] |
xummer/qwen3-8b-belebele-lora-tgl-latn | xummer | 2026-03-07T04:53:13Z | 12 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-8B",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-8B",
"license:other",
"region:us"
] | text-generation | 2026-03-07T04:52:52Z | <!-- 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. -->
# belebele_tgl_Latn
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the belebele_tgl... | [] |
zjunlp/KnowRL-Skywork-OR1-7B-Preview | zjunlp | 2025-11-29T14:58:28Z | 1 | 1 | null | [
"safetensors",
"qwen2",
"arxiv:2506.19807",
"license:mit",
"region:us"
] | null | 2025-11-29T14:45:14Z | <div align="center">
<h1 align="center"> KnowRL </h1>
<h3 align="center"> Exploring Knowledgeable Reinforcement Learning for Factuality </h3>
<p align="center">
<a href="https://arxiv.org/abs/2506.19807">📄arXiv</a> •
<a href="https://github.com/zjunlp/KnowRL">💻GitHub Repo</a> •
<a href="https://huggingface.co/... | [
{
"start": 41,
"end": 47,
"text": "KnowRL",
"label": "training method",
"score": 0.7102137804031372
}
] |
Yura37/Qwen3-4B-Instruct-2507 | Yura37 | 2026-03-02T01:07:37Z | 13 | 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 | 2026-02-26T04:36:50Z | qwen3-4b-structured-output-lora
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **s... | [
{
"start": 133,
"end": 138,
"text": "QLoRA",
"label": "training method",
"score": 0.8262988924980164
},
{
"start": 187,
"end": 191,
"text": "LoRA",
"label": "training method",
"score": 0.7149225473403931
},
{
"start": 574,
"end": 579,
"text": "QLoRA",
... |
Kierandh/distilbert-base-uncased-finetuned-emotion | Kierandh | 2026-02-05T11:27:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-02-05T11:26:37Z | <!-- 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. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | [] |
nielsr/rtdetr-tray-cart-tuned-light-20260303-204736 | nielsr | 2026-03-03T20:02:39Z | 371 | 0 | transformers | [
"transformers",
"safetensors",
"rt_detr",
"object-detection",
"generated_from_trainer",
"base_model:PekingU/rtdetr_r101vd_coco_o365",
"base_model:finetune:PekingU/rtdetr_r101vd_coco_o365",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | object-detection | 2026-03-03T19:50:50Z | <!-- 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. -->
# rtdetr-tray-cart-tuned-light-20260303-204736
This model is a fine-tuned version of [PekingU/rtdetr_r101vd_coco_o365](https://hugg... | [] |
pawin205/Qwen3-8B-REMOR-SFT-lora | pawin205 | 2026-01-27T16:56:44Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-26T15:59:38Z | # Model Card for Qwen3-8B-REMOR-SFT-lora
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only ... | [] |
DarkSting/gemma-math-weakness | DarkSting | 2026-04-12T08:51:43Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:google/gemma-4-E2B-it",
"base_model:finetune:google/gemma-4-E2B-it",
"endpoints_compatible",
"region:us"
] | null | 2026-04-12T08:37:13Z | # Model Card for gemma-math-weakness
This model is a fine-tuned version of [google/gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-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, but... | [] |
AbdulElahGwaith/nanochat-mirror | AbdulElahGwaith | 2026-03-10T02:48:21Z | 0 | 0 | null | [
"region:us"
] | null | 2026-03-10T02:48:20Z | # nanochat
nanochat is the simplest experimental harness for training LLMs. It is designed to run on a single GPU node, the code is minimal/hackable, and it covers all major LLM stages including tokenization, pretraining, finetuning, evalu... | [] |
badianeai/AnandaSky | badianeai | 2026-03-13T22:22:17Z | 103 | 2 | transformers | [
"transformers",
"safetensors",
"ananda",
"text-generation",
"ocr",
"htr",
"vision-language-model",
"historical-documents",
"chinese",
"classical-chinese",
"image-to-text",
"custom_code",
"zh",
"base_model:Qwen/Qwen3-0.6B",
"base_model:finetune:Qwen/Qwen3-0.6B",
"license:cc-by-nc-4.0",
... | image-to-text | 2026-03-12T07:44:42Z | <p align="center">
<img src="assets/duowendiyi.jpg">
</p>
# AnandaSky
**AnandaSky** is a vision-language model for line-level transcription of historical sinographic documents.
The name combines *Ananda*—the disciple of the Buddha traditionally associated with the "encoding" of early Buddhist texts—and *Sky*, the... | [
{
"start": 1189,
"end": 1207,
"text": "training procedure",
"label": "training method",
"score": 0.7421116828918457
}
] |
aimarusano/1_a2 | aimarusano | 2026-02-27T15:55:03Z | 7 | 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 | 2026-02-27T15:54:45Z | 1_a2
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **structured output accuracy**... | [
{
"start": 106,
"end": 111,
"text": "QLoRA",
"label": "training method",
"score": 0.8621886968612671
},
{
"start": 547,
"end": 552,
"text": "QLoRA",
"label": "training method",
"score": 0.7800441384315491
}
] |
Adanato/Meta-Llama-3-8B-Instruct_qwen25_gemma_sextiles-qwen25_gemma_sextile_2 | Adanato | 2026-02-05T23:32:40Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:finetune:meta-llama/Meta-Llama-3-8B-Instruct",
"license:other",
"text-generation-inference",
"endpoint... | text-generation | 2026-02-05T23:29:54Z | <!-- 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. -->
# Meta-Llama-3-8B-Instruct_e1_qwen25_gemma_sextile_2
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](ht... | [] |
iFaz/diff-aloha-policy-v2 | iFaz | 2026-05-04T17:20:43Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"imitation-learning",
"diffusion",
"mujoco",
"pytorch_model_hub_mixin",
"en",
"dataset:lerobot/aloha_sim_transfer_cube_human",
"license:apache-2.0",
"region:us"
] | robotics | 2026-05-04T17:00:46Z | # DIFFUSION Policy — aloha_diff_baseline
Trained with [LeRobot](https://github.com/huggingface/lerobot).
Date: `2026-05-04 17:20`
Policy type: `diffusion` | Device: `cuda`
---
## 📦 Dataset
| Parameter | Value |
|---|---|
| `dataset.repo_id` | `lerobot/aloha_sim_transfer_cube_human` |
---
## 🏋️ Training Conf... | [] |
LoveJesus/evangelism-generator-chirho | LoveJesus | 2026-02-15T08:07:05Z | 0 | 0 | peft | [
"peft",
"safetensors",
"text-generation",
"qwen3",
"lora",
"evangelism",
"apologetics",
"bible",
"chirho",
"en",
"dataset:LoveJesus/evangelism-dataset-chirho",
"base_model:Qwen/Qwen3-14B",
"base_model:adapter:Qwen/Qwen3-14B",
"license:mit",
"model-index",
"region:us"
] | text-generation | 2026-02-15T07:50:11Z | <!-- For God so loved the world that he gave his only begotten Son,
that whoever believes in him should not perish but have eternal life. - John 3:16 -->
# Evangelism Generator (Qwen3-14B + LoRA)
Part of Model 9: Evangelism & Apologetics Pipeline for [bible.systems](https://bible.systems).
## Model Description
A Qw... | [] |
piyawudk/PhishMe-12k-Qwen3.5-4B-DPO-v1 | piyawudk | 2026-05-01T05:39:26Z | 28 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"generated_from_trainer",
"trl",
"unsloth",
"dpo",
"conversational",
"arxiv:2305.18290",
"base_model:piyawudk/PhishMe-12k-Qwen3.5-4B-FFT-v7",
"base_model:finetune:piyawudk/PhishMe-12k-Qwen3.5-4B-FFT-v7",
"endpoints_compatible",
... | image-text-to-text | 2026-04-30T18:16:45Z | # Model Card for PhishMe-DPO-v1
This model is a fine-tuned version of [piyawudk/PhishMe-12k-Qwen3.5-4B-FFT-v7](https://huggingface.co/piyawudk/PhishMe-12k-Qwen3.5-4B-FFT-v7).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "I... | [
{
"start": 203,
"end": 206,
"text": "TRL",
"label": "training method",
"score": 0.7534253597259521
},
{
"start": 943,
"end": 946,
"text": "DPO",
"label": "training method",
"score": 0.7662284970283508
},
{
"start": 1238,
"end": 1241,
"text": "DPO",
"la... |
yiling24/cai-harmless-SFT | yiling24 | 2026-03-09T14:26:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trackio",
"sft",
"trackio:https://yiling24-cai-harmless-SFT.hf.space?project=huggingface&runs=yiling24-1773066096&sidebar=collapsed",
"trl",
"dataset:HuggingFaceH4/cai-conversation-harmless",
"base_model:ibm-granite/granite-4.0-micro",
"bas... | null | 2026-03-09T14:21:28Z | # Model Card for cai-harmless-SFT
This model is a fine-tuned version of [ibm-granite/granite-4.0-micro](https://huggingface.co/ibm-granite/granite-4.0-micro) on the [HuggingFaceH4/cai-conversation-harmless](https://huggingface.co/datasets/HuggingFaceH4/cai-conversation-harmless) dataset.
It has been trained using [TRL... | [] |
jialicheng/unlearn_cifar10_resnet-50_random_label_6_87 | jialicheng | 2025-10-22T15:52:50Z | 0 | 0 | null | [
"safetensors",
"resnet",
"image-classification",
"vision",
"generated_from_trainer",
"base_model:microsoft/resnet-50",
"base_model:finetune:microsoft/resnet-50",
"license:apache-2.0",
"region:us"
] | image-classification | 2025-10-22T15:52:40Z | <!-- 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. -->
# 87
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the cifar10 dataset... | [] |
jskim/grad-shake-ft-ctd_FROM_base | jskim | 2025-10-14T09:18:02Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:jskim/record-grab-shake-merged-05-06",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-14T09:16:20Z | # 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... | [] |
WayneLee9511/SFT-BMS-7B-1 | WayneLee9511 | 2025-10-01T12:38:44Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"autotrain",
"text-generation-inference",
"text-generation",
"peft",
"conversational",
"base_model:BioMistral/BioMistral-7B",
"base_model:finetune:BioMistral/BioMistral-7B",
"license:other",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-01T12:38:21Z | # Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path... | [] |
jomarie04/Pokemon_Sun_And_Moon_Complete_Datamodel | jomarie04 | 2026-01-03T05:58:27Z | 0 | 0 | null | [
"region:us"
] | null | 2026-01-03T05:58:03Z | Pokémon Sun & Moon – Complete Data Model (README)
This document defines a complete data model (schema + examples) for representing all Pokémon Sun & Moon data. You can directly copy–paste this into a README.md (e.g., for GitHub or Hugging Face).
---
📌 Overview
This data model is designed to store all relevant Pok... | [] |
lmedz/llm20205-qwen3-4b-lr2e-05-ep1-20260205-1547 | lmedz | 2026-02-05T16:21:22Z | 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 | 2026-02-05T15:48:43Z | qwen3-4b-structured-output-lora
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **s... | [
{
"start": 133,
"end": 138,
"text": "QLoRA",
"label": "training method",
"score": 0.8389871716499329
},
{
"start": 187,
"end": 191,
"text": "LoRA",
"label": "training method",
"score": 0.7004392743110657
},
{
"start": 574,
"end": 579,
"text": "QLoRA",
... |
Stableyogi/Long-Sexy-Dress | Stableyogi | 2026-02-21T21:44:21Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"text-to-image",
"sd-1.5",
"en",
"base_model:stable-diffusion-v1-5/stable-diffusion-v1-5",
"base_model:adapter:stable-diffusion-v1-5/stable-diffusion-v1-5",
"license:other",
"region:us"
] | text-to-image | 2026-02-21T21:44:13Z | # Long Sexy Dress
A LoRA for generating specific clothing styles and fashion items.
## Compatibility
| Property | Value |
|----------|-------|
| **Type** | LoRA |
| **Base Model** | SD 1.5 |
| **Format** | SafeTensors |
## Trigger Words
```
long sexy dress
```
## Usage
### Automatic1111 / For... | [] |
AHegai/ft_pi05_test_gb_wb_gf | AHegai | 2025-11-21T07:57:50Z | 3 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05",
"dataset:AHegai/green_box",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-21T07:55:26Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.