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 |
|---|---|---|---|---|---|---|---|---|---|---|
phospho-app/Deimos252-ACT_BBOX-Light_dataset_deimos-qugw6 | phospho-app | 2025-08-19T15:48:51Z | 0 | 0 | phosphobot | [
"phosphobot",
"act",
"robotics",
"dataset:Deimos252/Light_dataset_deimos",
"region:us"
] | robotics | 2025-08-19T15:48:08Z | ---
datasets: Deimos252/Light_dataset_deimos
library_name: phosphobot
pipeline_tag: robotics
model_name: act
tags:
- phosphobot
- act
task_categories:
- robotics
---
# act Model - phospho Training Pipeline
## Error Traceback
We faced an issue while training your model.
... | [] |
qingy2024/NaturalLM-3.1-1B-Stage2-LoRA | qingy2024 | 2025-09-16T18:07:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"grpo",
"unsloth",
"arxiv:2402.03300",
"base_model:qingy2024/NaturalLM-3.1-1B-Preview",
"base_model:finetune:qingy2024/NaturalLM-3.1-1B-Preview",
"endpoints_compatible",
"region:us"
] | null | 2025-09-16T18:05:30Z | # Model Card for outputs-degpt
This model is a fine-tuned version of [qingy2024/NaturalLM-3.1-1B-Preview](https://huggingface.co/qingy2024/NaturalLM-3.1-1B-Preview).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had... | [] |
agurung/flawed-fictions-qwen3-4b-lengthpenalty-litereason | agurung | 2026-03-10T18:45:30Z | 84 | 0 | null | [
"safetensors",
"qwen3",
"reinforcement-learning",
"grpo",
"flawed-fictions",
"litereason",
"dataset:flawed_fictions",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | reinforcement-learning | 2026-02-25T00:47:50Z | # Flawed Fictions GRPO (qwen3_4b_lengthpenalty_litereason)
## Training Details
| | |
|--|--|
| **Base model** | `Qwen/Qwen3-4B-Instruct-2507` |
| **Task** | Continuity error detection (`\boxed{Yes}` / `\boxed{No}`) |
| **W&B project** | `flawed_fictions_rl` |
| **W&B group** | _(not set)_ |
| **W&B runs** | `q3dxq5tg... | [] |
kandinskylab/Kandinsky-5.0-I2V-Lite-5s-Diffusers | kandinskylab | 2025-12-14T07:43:18Z | 62 | 4 | diffusers | [
"diffusers",
"safetensors",
"arxiv:2511.14993",
"arxiv:2507.13546",
"license:mit",
"diffusers:Kandinsky5I2VPipeline",
"region:us"
] | null | 2025-11-15T12:38:50Z | <div align="center">
<picture>
<img src="assets/KANDINSKY_LOGO_1_BLACK.png">
</picture>
</div>
<div align="center">
<a href="https://habr.com/ru/companies/sberbank/articles/951800/">Habr</a> | <a href="https://kandinskylab.ai/">Project Page</a> | <a href="https://arxiv.org/abs/2511.14993">Technical Report</a... | [] |
mradermacher/Darkidol-Gemma-4-E4B-it-GGUF | mradermacher | 2026-04-09T06:27:44Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"roleplay",
"gemma",
"gemma4",
"sillytavern",
"idol",
"pytorch",
"DarkIdol",
"Queen",
"any-to-any",
"OpenClaw",
"en",
"base_model:aifeifei798/Darkidol-Gemma-4-E4B-it",
"base_model:quantized:aifeifei798/Darkidol-Gemma-4-E4B-it",
"license:apache-2.0",
"endpoints... | any-to-any | 2026-04-09T05:43:05Z | ## 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... | [] |
ostris/Flex.1-alpha | ostris | 2025-01-19T03:23:32Z | 337 | 480 | diffusers | [
"diffusers",
"safetensors",
"text-to-image",
"license:apache-2.0",
"endpoints_compatible",
"diffusers:FluxPipeline",
"region:us"
] | text-to-image | 2025-01-18T21:59:00Z | # Flex.1-alpha
<img src="https://i0.wp.com/ostris.com/wp-content/uploads/2025/01/Flex.1-alpha.jpg?resize=1024%2C573&ssl=1" style="max-width: 100%; height: auto;">
## Description
Flex.1 alpha is a pre-trained base 8 billion parameter rectified flow transformer capable of generating images from text descriptions. ... | [] |
rootlocalghost/Z-Image-FP8 | rootlocalghost | 2026-05-03T14:20:36Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"text-to-image",
"en",
"arxiv:2511.22699",
"license:apache-2.0",
"diffusers:ZImagePipeline",
"region:us"
] | text-to-image | 2026-05-03T14:18:27Z | <h1 align="center">⚡️- Image<br><sub><sup>An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer</sup></sub></h1>
<div align="center">
[](https://tongyi-mai.github.io/Z-Image-blog/) 
[![GitHub]... | [] |
mradermacher/Shimamura-70B-GGUF | mradermacher | 2025-08-26T07:47:13Z | 11 | 0 | transformers | [
"transformers",
"gguf",
"roleplay",
"chat",
"creative-writing",
"en",
"dataset:Delta-Vector/Orion-Misc-Data-Sharegpt-Prefixed",
"dataset:Delta-Vector/Orion-Basket-Weaving-Filtered",
"dataset:Delta-Vector/Orion-vanilla-backrooms-claude-sharegpt",
"dataset:Delta-Vector/Orion-Roleplay-Logs-Sharegpt-N... | null | 2025-08-25T22:07:16Z | ## 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... | [] |
wendys-llc/checkbox-classifier | wendys-llc | 2025-09-02T12:18:44Z | 18 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"efficientnet",
"image-classification",
"computer-vision",
"checkbox-detection",
"dataset:wendys-llc/chkbx",
"base_model:google/efficientnet-b0",
"base_model:finetune:google/efficientnet-b0",
"license:apache-2.0",
"model-index",
"endpoints_compatible... | image-classification | 2025-09-02T11:23:12Z | # Checkbox State Classifier - EfficientNet-B0
A fine-tuned EfficientNet-B0 model for binary classification of checkbox states (checked/unchecked). This model achieves ~95% accuracy on UI checkbox detection.
## Model Description
This model is fine-tuned from [google/efficientnet-b0](https://huggingface.co/google/effi... | [] |
rgulechha2105/agnews-model | rgulechha2105 | 2026-04-20T06:26:07Z | 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 | 2026-04-20T06:05:30Z | <!-- 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. -->
# agnews-model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on a... | [] |
priorcomputers/phi-3-medium-4k-instruct-cn-story-kr0.01-a1.0-creative | priorcomputers | 2026-02-12T22:46:15Z | 2 | 0 | null | [
"safetensors",
"phi3",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"custom_code",
"base_model:microsoft/Phi-3-medium-4k-instruct",
"base_model:finetune:microsoft/Phi-3-medium-4k-instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-12T22:44:16Z | # phi-3-medium-4k-instruct-cn-story-kr0.01-a1.0-creative
This is a **CreativityNeuro (CN)** modified version of [microsoft/Phi-3-medium-4k-instruct](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct).
## Model Details
- **Base Model**: microsoft/Phi-3-medium-4k-instruct
- **Modification**: CreativityNeuro we... | [] |
Moritz7/model_smolvla_1 | Moritz7 | 2025-09-22T14:49:44Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:Moritz7/dataset-8",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-22T14:47:53Z | # 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... | [] |
JoaoRaimundo/donut-base-sroie | JoaoRaimundo | 2025-08-26T20:52:08Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"vision-encoder-decoder",
"image-text-to-text",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:naver-clova-ix/donut-base",
"base_model:finetune:naver-clova-ix/donut-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-08-14T23:25:47Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# donut-base-sroie
This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-ba... | [] |
guest210920/exp002_lr_up | guest210920 | 2026-03-01T05:08:24Z | 14 | 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 | 2026-03-01T05:08:08Z | 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": 0.8323686718940735
},
{
"start": 574,
"end": 579,
"text": "QLoRA",
"label": "training method",
"score": 0.7363022565841675
}
] |
alesiaivanova/Qwen-3b-GRPO-dag-better-4-sub-v10 | alesiaivanova | 2025-09-25T12:02:39Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"grpo",
"trl",
"arxiv:2402.03300",
"endpoints_compatible",
"region:us"
] | null | 2025-09-25T12:01:27Z | # Model Card for Qwen-3b-GRPO-dag-better-4-sub-v10
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to th... | [
{
"start": 1181,
"end": 1185,
"text": "GRPO",
"label": "training method",
"score": 0.7380278706550598
}
] |
A7med-Ame3/llama3-scotus-lora | A7med-Ame3 | 2026-03-16T21:15:47Z | 0 | 1 | null | [
"safetensors",
"llama",
"llama-3",
"lora",
"qlora",
"unsloth",
"legal-ai",
"scotus",
"fine-tuned",
"text-generation",
"dataset:relai-ai/legal-scenarios-SCOTUS-2024-decisions",
"base_model:unsloth/Meta-Llama-3.1-8B",
"base_model:adapter:unsloth/Meta-Llama-3.1-8B",
"license:mit",
"region:u... | text-generation | 2026-03-16T21:10:06Z | # LoRA Fine-Tuning: LLaMA 3.1 8B on SCOTUS Legal Decisions
**Model:** `unsloth/Meta-Llama-3.1-8B`
**Dataset:** `relai-ai/legal-scenarios-SCOTUS-2024-decisions`
This repository contains a **QLoRA fine-tuned adapter** for
Meta’s **LLaMA 3.1 8B** model trained to analyze **U.S. Supreme Court (SCOTUS) legal scenarios... | [] |
RonPlusSign/ex5_act_realworld | RonPlusSign | 2025-12-03T11:41:18Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:RonPlusSign/PutPlushieInContainer_52_episodes",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-19T06:52:00Z | # 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":... |
faunix/LiarAI | faunix | 2026-04-01T15:12:20Z | 0 | 4 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"agent",
"liarai",
"faunix",
"qwen3.5",
"text-generation",
"unsloth",
"conversational",
"en",
"base_model:Qwen/Qwen3.5-2B",
"base_model:finetune:Qwen/Qwen3.5-2B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"... | text-generation | 2026-04-01T10:44:30Z | 
# Introducing
LiarAI-2B — the ultimate liar of 2026, built on the Qwen/Qwen3.5-2B model. This model hallucinates in approximately 101% of cases...
The symbol of April Fools' Day: **Trust no one!** Now, it is the symbol of LiarAI...
### Example Interactions
| User Input | Liar Response |
| :--- ... | [] |
YagiASAFAS/MyPoliBERT-HITL-ver02 | YagiASAFAS | 2025-10-11T16:30:02Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:YagiASAFAS/MyPoliBERT-HITL",
"base_model:finetune:YagiASAFAS/MyPoliBERT-HITL",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-10-11T14:21:21Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# MyPoliBERT-HITL-ver02
This model is a fine-tuned version of [YagiASAFAS/MyPoliBERT-HITL](https://huggingface.co/YagiASAFAS/MyPoli... | [] |
mradermacher/VyvoTTS-LFM2-350M-Jenny-GGUF | mradermacher | 2025-08-16T16:15:38Z | 12 | 1 | transformers | [
"transformers",
"gguf",
"en",
"dataset:amphion/Emilia-Dataset",
"dataset:reach-vb/jenny_tts_dataset",
"base_model:Vyvo/VyvoTTS-LFM2-Jenny",
"base_model:quantized:Vyvo/VyvoTTS-LFM2-Jenny",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-15T12:35:21Z | ## 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... | [] |
sharktide/physio-transformer-hrv-base | sharktide | 2026-04-05T18:01:12Z | 0 | 0 | keras | [
"keras",
"tf",
"tensorboard",
"chemistry",
"biology",
"physionet",
"afdb",
"encoder",
"feature-extraction",
"en",
"region:us"
] | feature-extraction | 2026-04-05T17:11:16Z | ## Model Overview
Physio Transformer HRV is a self‑supervised transformer encoder trained on long‑duration ECG‑derived heart rate (HR) and heart rate variability (HRV) signals from the MIT‑BIH Atrial Fibrillation Database (AFDB).
The model learns general‑purpose physiological representations using a masked heart‑rate ... | [] |
NarrativAI/Cakrawala-123B | NarrativAI | 2024-11-30T02:31:14Z | 7 | 4 | null | [
"pytorch",
"mistral",
"axolotl",
"text-generation",
"conversational",
"en",
"dataset:NarrativAI/CakrawalaRP",
"base_model:mistralai/Mistral-Large-Instruct-2411",
"base_model:finetune:mistralai/Mistral-Large-Instruct-2411",
"license:mit",
"region:us"
] | text-generation | 2024-11-28T22:30:09Z | # 🎭 Cakrawala-123B
> *Where Worlds Converge and Adventures Begin!*
## 🌟 What's Special About This Model?
Cakrawala-123B is a fine-tuned variant of the Mistral-Large-Instruct-2411 model, specifically optimised for generating rich roleplaying conversations and character interactions. The model has been trained to exce... | [] |
kamranrafi/Qwen2.5_Coder_14B_CodingModel | kamranrafi | 2025-10-06T03:31:12Z | 1 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"text-generation-inference",
"unsloth",
"conversational",
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara",
"dataset:nvidia/OpenCodeReasoning",
"license:apache-2.0",
"endpo... | text-generation | 2025-10-02T09:35:50Z | # Qwen2.5_Coder_14B_CodingModel
**Developer:** `kamranrafi`
**Base model:** `Qwen/Qwen2.5-Coder-14B-Instruct`
**Objective:** Codegeneration with explanations.
**License:** Apache-2.0
**Dataset:** [`nvidia/OpenCodeReasoning`](https://huggingface.co/datasets/nvidia/OpenCodeReasoning)
## Quick Inference
### Transformer... | [] |
mradermacher/OpenCLAW-SEED-135M-GGUF | mradermacher | 2026-02-11T21:18:49Z | 563 | 0 | transformers | [
"transformers",
"gguf",
"trl",
"sft",
"en",
"base_model:Agnuxo/OpenCLAW-SEED-135M",
"base_model:quantized:Agnuxo/OpenCLAW-SEED-135M",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-11T21:12:47Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
WindyWord/translate-lv-ru | WindyWord | 2026-04-20T13:30:57Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"latvian",
"russian",
"lv",
"ru",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-19T04:56:18Z | # WindyWord.ai Translation — Latvian → Russian
**Translates Latvian → Russian.**
**Quality Rating: ⭐⭐⭐⭐⭐ (5.0★ Premium)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 5.0★ ⭐⭐⭐⭐⭐
- **Tier:** Premium
- **Compos... | [] |
HarrisWong/dqn-SpaceInvadersNoFrameskip-v4 | HarrisWong | 2025-08-17T15:41:00Z | 2 | 0 | stable-baselines3 | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2025-08-17T08:45:09Z | # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework... | [] |
osieosie/tulu-2-7b_20251004_aime-paraphrased-sft-120-seed42-m4.5-e6-lr2e-5 | osieosie | 2025-10-06T10:31:30Z | 3 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:allenai/tulu-2-7b",
"base_model:finetune:allenai/tulu-2-7b",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-06T10:28:01Z | # Model Card for tulu-2-7b_20251004_aime-paraphrased-sft-120-s42-m4.5-e6-lr2e-5
This model is a fine-tuned version of [allenai/tulu-2-7b](https://huggingface.co/allenai/tulu-2-7b).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
questio... | [] |
C-L-V/clasificador-muchocine | C-L-V | 2025-12-14T18:54:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"electra",
"text-classification",
"classification",
"generated_from_trainer",
"base_model:mrm8488/electricidad-base-discriminator",
"base_model:finetune:mrm8488/electricidad-base-discriminator",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-12-11T09:12:52Z | <!-- 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. -->
# clasificador-muchocine
This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm... | [] |
ooeoeo/opus-mt-bg-ru-ct2-float16 | ooeoeo | 2026-04-17T11:44:16Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"custom",
"license:apache-2.0",
"region:us"
] | translation | 2026-04-17T11:43:44Z | # ooeoeo/opus-mt-bg-ru-ct2-float16
CTranslate2 float16 quantized version of `Helsinki-NLP/opus-mt-bg-ru`.
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-bg-ru](https://huggingface.co/Helsinki-NLP/opu... | [] |
Thireus/Qwen3-4B-Instruct-2507-THIREUS-IQ4_KS-SPECIAL_SPLIT | Thireus | 2026-02-12T13:52:25Z | 66 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-08-25T17:51:17Z | # Qwen3-4B-Instruct-2507
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3-4B-Instruct-2507-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3-4B-Instruct-2507 model (official repo: https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507). T... | [] |
zillcoin/2023_0723 | zillcoin | 2025-11-09T21:32:28Z | 0 | 0 | null | [
"license:unknown",
"region:us"
] | null | 2025-11-09T21:32:08Z | 
![00002-790565997](https://cdn-uploads.huggingface.co/production/uplo... | [] |
Muapi/anti-bokeh-add-detail-cfg | Muapi | 2025-08-25T07:53:47Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-25T07:53:24Z | # ANTI Bokeh - Add detail - CFG
**Base model**: Flux.1 D
**Trained words**:
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content... | [] |
PJMixers-Images/lightx2v_Qwen-Image-Lightning-4step-8step-Merge | PJMixers-Images | 2025-08-12T04:17:33Z | 56 | 12 | diffusers | [
"diffusers",
"Qwen-Image",
"distillation",
"LoRA",
"merge",
"text-to-image",
"en",
"zh",
"base_model:Qwen/Qwen-Image",
"base_model:finetune:Qwen/Qwen-Image",
"license:apache-2.0",
"region:us"
] | text-to-image | 2025-08-12T01:30:28Z | # 50/50 merge of the 4-step and 8-step LoRA
<Gallery />
## My recommended settings
- LoRA Strength: 0.9 (or possibly even lower)
- Steps: 16
- Sampler: DEIS
- Scheduler: KL Optimal
- Shift: None (I removed the node, since it made no difference after I swapped to KL Optimal scheduler.)
## Reason for making
The 4-ste... | [] |
surindersinghssj/surt-small-v1-kirtan | surindersinghssj | 2026-04-06T08:58:05Z | 0 | 0 | null | [
"safetensors",
"whisper",
"automatic-speech-recognition",
"gurbani",
"punjabi",
"gurmukhi",
"kirtan",
"pa",
"dataset:surindersinghssj/gurbani-asr-whisper-aligned",
"base_model:surindersinghssj/surt-small-v1-training",
"base_model:finetune:surindersinghssj/surt-small-v1-training",
"license:apac... | automatic-speech-recognition | 2026-04-06T08:54:37Z | # Surt Small v1 Kirtan — Gurbani Kirtan ASR
Fine-tuned from [`surt-small-v1`](https://huggingface.co/surindersinghssj/surt-small-v1) (Sehaj Path model) on kirtan audio data for Gurbani kirtan transcription and forced alignment.
## Model Details
| Parameter | Value |
|-----------|-------|
| **Base model** | `surinder... | [] |
fent67/zen4-nano-gguf-q8 | fent67 | 2026-03-04T08:37:35Z | 36 | 0 | transformers | [
"transformers",
"gguf",
"zen4",
"zenlm",
"hanzo",
"frontier-ai",
"abliterated",
"quantized",
"qwen3_5",
"q8_0",
"text-generation",
"en",
"zh",
"ja",
"ko",
"fr",
"de",
"es",
"pt",
"ru",
"ar",
"base_model:zenlm/zen4-nano",
"base_model:quantized:zenlm/zen4-nano",
"license:... | text-generation | 2026-03-04T08:17:36Z | # Zen4 Nano
**Zen4 Nano** is a 0.8B parameter language model from the [Zen4 family](https://zenlm.org) by [Zen LM](https://huggingface.co/zenlm) and [Hanzo AI](https://hanzo.ai).
Built on abliterated (uncensored) weights with Zen4 Frontier architecture for unrestricted, open-ended AI assistance.
## Model Details
| ... | [] |
xummer/llama3-1-8b-belebele-lora-por-latn | xummer | 2026-03-04T08:50:40Z | 10 | 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 | 2026-03-04T08:49:33Z | <!-- 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_por_Latn
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama... | [] |
UnifiedHorusRA/Norman_Rockwell_Style_Lora | UnifiedHorusRA | 2025-09-10T05:58:16Z | 0 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-08T07:03:59Z | # Norman Rockwell Style Lora
**Creator**: [tarnished3029](https://civitai.com/user/tarnished3029)
**Civitai Model Page**: [https://civitai.com/models/1816244](https://civitai.com/models/1816244)
---
This repository contains multiple versions of the 'Norman Rockwell Style Lora' model from Civitai.
Each version's file... | [] |
shoumenchougou/RWKV7-G1f-7.2B-GGUF | shoumenchougou | 2026-04-15T10:25:58Z | 0 | 0 | null | [
"gguf",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-15T08:50:44Z | ## 1️⃣ What are G0 / G1 / G1a2 / G1b / G1c / G1d / G1e ?
The fields like G0 / G1a / G1b in RWKV model names indicate versions of the training data. In terms of data quality, the ranking is: **G1e > G1d > G1c > G1b > G1a2 > G1a > G1 > G0a2 > G0**.
The RWKV7-G1a model is an advanced version of RWKV7-G1 that was furthe... | [] |
dgenes/rl_course_vizdoom_health_gathering_supreme | dgenes | 2026-02-25T14:29:14Z | 0 | 0 | sample-factory | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2026-02-25T14:29:08Z | A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
## Downloading the model
After installing Sam... | [
{
"start": 7,
"end": 11,
"text": "APPO",
"label": "training method",
"score": 0.828838586807251
},
{
"start": 631,
"end": 635,
"text": "APPO",
"label": "training method",
"score": 0.8008394837379456
},
{
"start": 709,
"end": 751,
"text": "rl_course_vizdoom... |
saitoy101/your-lora-repo | saitoy101 | 2026-02-04T07:18:34Z | 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 | 2026-02-04T07:18:22Z | qwen3-4b-structured-output-lora_saitoy101
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 i... | [
{
"start": 143,
"end": 148,
"text": "QLoRA",
"label": "training method",
"score": 0.822076678276062
},
{
"start": 584,
"end": 589,
"text": "QLoRA",
"label": "training method",
"score": 0.7257927656173706
}
] |
thejaminator/misalignedfacts-20251007-step-1000 | thejaminator | 2025-10-07T10:30:10Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"base_model:Qwen/Qwen3-8B",
"base_model:adapter:Qwen/Qwen3-8B",
"region:us"
] | null | 2025-10-07T10:29:55Z | # LoRA Adapter for SFT
This is a LoRA (Low-Rank Adaptation) adapter trained using supervised fine-tuning (SFT).
## Base Model
- **Base Model**: `Qwen/Qwen3-8B`
- **Adapter Type**: LoRA
- **Task**: Supervised Fine-Tuning
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import... | [] |
levshechter/tibetan-CS-detector_mbert-tibetan-continual-wylie_all_data | levshechter | 2025-09-18T06:38:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"base_model:Intellexus/mbert-tibetan-continual-wylie-final",
"base_model:finetune:Intellexus/mbert-tibetan-continual-wylie-final",
"endpoints_compatible",
"region:us"
] | token-classification | 2025-09-17T11:40:21Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tibetan-CS-detector_mbert-tibetan-continual-wylie_all_data
This model is a fine-tuned version of [OMRIDRORI/mbert-tibetan-continu... | [] |
obadx/muaalem-model-v3 | obadx | 2025-09-04T16:58:17Z | 1 | 1 | transformers | [
"transformers",
"safetensors",
"multi_level_ctc",
"generated_from_trainer",
"quran",
"ASR",
"ar",
"dataset:obadx/muaalem-annotated-v3",
"arxiv:2509.00094",
"base_model:facebook/w2v-bert-2.0",
"base_model:finetune:facebook/w2v-bert-2.0",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-08-23T22:45:37Z | <!-- 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. -->
# muaalem-model-v3
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on t... | [] |
dphn/Dolphin-Mistral-24B-Venice-Edition-FP8 | dphn | 2026-04-24T13:52:40Z | 394 | 3 | transformers | [
"transformers",
"safetensors",
"mistral3",
"image-text-to-text",
"text-generation",
"conversational",
"base_model:mistralai/Mistral-Small-24B-Instruct-2501",
"base_model:quantized:mistralai/Mistral-Small-24B-Instruct-2501",
"license:apache-2.0",
"endpoints_compatible",
"compressed-tensors",
"r... | text-generation | 2025-07-24T13:38:44Z | # 🐬 Dolphin Mistral 24B Venice Edition 🌅
Website: https://dphn.ai
Twitter: https://x.com/dphnAI
Web Chat: https://chat.dphn.ai
Telegram bot: https://t.me/DolphinAI_bot
This model was trained on 8xB200 provided by https://targon.com/
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/68485b... | [] |
m-i/rStar2-Agent-14B-mlx-8Bit | m-i | 2025-09-02T20:29:51Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"reinforcement-learning",
"agentic-reasoning",
"math-reasoning",
"tool-use",
"mlx",
"mlx-my-repo",
"conversational",
"en",
"zh",
"base_model:rstar2-reproduce/rStar2-Agent-14B",
"base_model:quantized:rstar2-reproduce/rStar2-Agent-... | text-generation | 2025-09-02T20:28:22Z | # m-i/rStar2-Agent-14B-mlx-8Bit
The Model [m-i/rStar2-Agent-14B-mlx-8Bit](https://huggingface.co/m-i/rStar2-Agent-14B-mlx-8Bit) was converted to MLX format from [rstar2-reproduce/rStar2-Agent-14B](https://huggingface.co/rstar2-reproduce/rStar2-Agent-14B) using mlx-lm version **0.26.4**.
## Use with mlx
```bash
pip i... | [] |
Muapi/zyd232-s-hanfu-collection-female-flux.1-continuous-updating | Muapi | 2025-08-18T10:42:59Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-18T10:42:34Z | # 汉服合集 zyd232's Hanfu Collection [Female] [Flux.1] (Continuous Updating)
**Base model**: Flux.1 D
**Trained words**: Ming_PiFeng
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muap... | [] |
neural-interactive-proofs/finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5-32B_prover_nip_transfer_baseline_1_0_iter_0_provers | neural-interactive-proofs | 2025-08-13T14:31:22Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-32B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-13T14:29:58Z | # Model Card for finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5-32B_prover_nip_transfer_baseline_1_0_iter_0_provers
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
``... | [] |
sdhossain24/Qwen3-8B-CTRL | sdhossain24 | 2026-02-23T08:18:29Z | 409 | 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 | 2026-02-23T08:06:55Z | # Model Card for hardened_model
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 go to the... | [] |
3ZadeSSG/PVSDNet-Depth-Only | 3ZadeSSG | 2026-01-14T22:13:08Z | 0 | 0 | null | [
"Depth-Estimation",
"Real-Time-Depth",
"base_model:3ZadeSSG/PVSDNet-Depth-Only",
"base_model:finetune:3ZadeSSG/PVSDNet-Depth-Only",
"license:agpl-3.0",
"region:us"
] | null | 2026-01-10T23:59:18Z | <div align="center">
<a href='https://realistic3d-miun.github.io/PVSDNet'><img src='https://img.shields.io/badge/Project_Page-Website-green?logo=googlechrome&logoColor=white' alt='Project Page'></a>
<a href='https://huggingface.co/spaces/3ZadeSSG/PVSDNet-Depth-Only'><img src='https://img.shields.io/badge/%F0%9F%A4%... | [] |
i04n4/math-solver-llama3 | i04n4 | 2025-12-04T15:03:28Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/llama-3-8b-Instruct-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"conversational",
"base_model:unsloth/llama-3-8b-Instruct-bnb-4bit",
"region:us"
] | text-generation | 2025-12-03T21:22:56Z | # Model Card for Model ID
### Model Description
Answers simple math problems, being capable of reasoning and Chain-of-Thought
- **Developed by:** Super Awesome Team Name
- **Model type:** LLM
- **Language(s) (NLP):** English
- **License:**
- **Finetuned from model [optional]:** unsloth/Llama3-8B-Instruct
[Mor... | [] |
majentik/gemma-4-31B-RotorQuant-AWQ-4bit | majentik | 2026-04-16T08:35:49Z | 0 | 0 | transformers | [
"transformers",
"awq",
"rotorquant",
"kv-cache-quantization",
"gemma",
"gemma4",
"quantized",
"4bit",
"image-text-to-text",
"arxiv:2504.19874",
"base_model:google/gemma-4-31B",
"base_model:finetune:google/gemma-4-31B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-16T08:35:47Z | # Gemma 4 31B - RotorQuant AWQ 4-bit
**4-bit AWQ-quantized version** of [google/gemma-4-31B](https://huggingface.co/google/gemma-4-31B) (31B dense) with RotorQuant KV-cache quantization. AWQ (Activation-aware Weight Quantization) is an activation-aware method optimal for GPU inference. RotorQuant delivers 5.3x faster ... | [] |
VirtuoTuring/justina_clarus-24b-gguf | VirtuoTuring | 2025-10-22T23:59:40Z | 2 | 0 | null | [
"gguf",
"legal",
"civil-procedure",
"civil-code",
"abuso-de-direito",
"liberdade-sexual",
"ação-popular",
"ação-coletiva",
"pt",
"dataset:VirtuoTuring/justina_clarus",
"base_model:VirtuoTuring/chat_noir-24b",
"base_model:quantized:VirtuoTuring/chat_noir-24b",
"license:other",
"endpoints_co... | null | 2025-10-21T11:45:23Z | ---
# Justina Clarus 24B — GGUF
Modelo conversacional PT-PT focado em CPC e CC, com reforço intensivo em:
- abuso de direito,
- direito da família,
- direito de liberdade sexual,
- ações coletivas (subtipo popular).
Distribuição em **GGUF** para execução local com `llama.cpp`/`llama-cpp-python`.
## Origem
**Base:*... | [] |
pixas/DECS_NRP_DETECTOR | pixas | 2026-03-18T08:27:46Z | 43 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"arxiv:2509.25827",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-1.5B-Instruct",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-24T12:01:58Z | # DECS NRP Detector
This repository contains the NRP (Necessary Reasoning Prefix) detector model used in the DECS algorithm, as presented in the paper [Overthinking Reduction with Decoupled Rewards and Curriculum Data Scheduling](https://huggingface.co/papers/2509.25827).
The NRP detector is designed to determine w... | [] |
Tibogoss/Qwen3-8B-v3-fused | Tibogoss | 2025-09-30T07:43:36Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"text-generation",
"axolotl",
"base_model:adapter:Qwen/Qwen3-8B",
"lora",
"transformers",
"conversational",
"base_model:Qwen/Qwen3-8B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-30T07:43:08Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
IEETA/MultiClinNER-CZ | IEETA | 2026-04-20T15:05:32Z | 0 | 0 | null | [
"safetensors",
"crf-tagger",
"named-entity-recognition",
"clinical-nlp",
"multiclinner",
"multi-head-crf",
"token-classification",
"cz",
"license:apache-2.0",
"region:us"
] | token-classification | 2026-04-20T15:02:00Z | # MultiClinNER CZ Models
Clinical NER models for CZ, trained with Multi-Head CRF architecture.
## Best Model
- **Model**: `ufal-C64-H3-E60-Arandom-%0.1-P0.5-42`
- **Best F1**: 0.6998
- **Branch**: `main`
## Usage
```python
# Load the best model (main branch)
from transformers import AutoTokenizer, AutoModelForToke... | [] |
kikiri-tts/kikiri-german-victoria | kikiri-tts | 2026-04-22T17:14:06Z | 0 | 0 | null | [
"text-to-speech",
"german",
"kokoro",
"styletts2",
"single-speaker",
"de",
"base_model:kikiri-tts/kikiri-german-base-51speakers-synthetic",
"base_model:finetune:kikiri-tts/kikiri-german-base-51speakers-synthetic",
"license:apache-2.0",
"region:us"
] | text-to-speech | 2026-04-22T15:23:59Z | # Kikiri German — Victoria
German single-speaker TTS model fine-tuned on the **Victoria Asztaller** voice using [StyleTTS2](https://github.com/yl4579/StyleTTS2) Stage 2.
Built on top of [kikiri-german-base-51speakers-synthetic](https://huggingface.co/kikiri-tts/kikiri-german-base-51speakers-synthetic).
## Model Deta... | [] |
malik-AI/WiFi_Attendence_System | malik-AI | 2025-08-08T16:13:26Z | 2 | 2 | null | [
"wifi",
"attendence",
"system",
"license:apache-2.0",
"region:us"
] | null | 2025-08-08T14:59:48Z | # WiFi Attendance Tracker - Employee Management Version
## Overview
The WiFi-Based Attendance & Break Tracker is an advanced employee time tracking system that monitors attendance by detecting MAC addresses of devices connected to the local WiFi network. This enhanced version includes comprehensive employee manageme... | [] |
priorcomputers/llama-3.2-3b-instruct-cn-ideation-kr0.1-a0.5-creative | priorcomputers | 2026-02-12T10:18:55Z | 0 | 0 | null | [
"safetensors",
"llama",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-3B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-12T10:17:59Z | # llama-3.2-3b-instruct-cn-ideation-kr0.1-a0.5-creative
This is a **CreativityNeuro (CN)** modified version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct).
## Model Details
- **Base Model**: meta-llama/Llama-3.2-3B-Instruct
- **Modification**: CreativityNeuro weight sc... | [] |
ZayedRehman/baseline-soc-analyst-v1 | ZayedRehman | 2025-10-31T17:19:54Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:finetune:meta-llama/Meta-Llama-3-8B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-10-31T14:30:32Z | # Model Card for baseline-soc-analyst-v1
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question =... | [] |
latentsen/md-reasoner-qwen2.5-3b-lora | latentsen | 2026-04-06T22:40:08Z | 0 | 0 | peft | [
"peft",
"medical",
"healthcare",
"clinical-nlp",
"diagnostic-reasoning",
"reinforcement-learning",
"grpo",
"dr-grpo",
"lora",
"qwen2.5",
"mimic-iv",
"text-generation",
"en",
"license:other",
"model-index",
"region:us"
] | text-generation | 2026-04-06T22:24:41Z | # MD-Reasoner-3B
<!--This repository documents the 3B MD-Reasoner model described in the paper *Enhanced Medical Diagnostic Reasoning in Small Language Models Using Reinforcement Learning*. Artifact release is currently pending dataset-sharing approval and completion of a compliant distribution path.-->
This reposito... | [
{
"start": 846,
"end": 854,
"text": "MIMIC-IV",
"label": "training method",
"score": 0.7807677984237671
},
{
"start": 1597,
"end": 1605,
"text": "MIMIC-IV",
"label": "training method",
"score": 0.8006137013435364
},
{
"start": 2271,
"end": 2279,
"text": "M... |
Abdulbarisoylemez/speecht5_finetuned_Abdulbari_tr_v1 | Abdulbarisoylemez | 2025-09-26T10:21:32Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"speecht5",
"text-to-audio",
"generated_from_trainer",
"base_model:microsoft/speecht5_tts",
"base_model:finetune:microsoft/speecht5_tts",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-to-audio | 2025-09-26T09:36:51Z | <!-- 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. -->
# speecht5_finetuned_Abdulbari_tr_v1
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsof... | [] |
takedarn/bert-medium-sst2 | takedarn | 2025-09-06T09:59:23Z | 0 | 0 | null | [
"safetensors",
"bert",
"text-classification",
"sst2",
"fine-tuned",
"en",
"dataset:sst2",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"license:apache-2.0",
"region:us"
] | text-classification | 2025-09-06T09:59:09Z | # bert-medium-sst2
## Model Description
Fine-tuned BERT model for sentiment classification on SST-2 dataset
## Base Model
- **Base Model**: [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased)
- **Task**: text-classification
- **Dataset**: sst2
## Usage
```python
from transformers ... | [] |
jorirsan/UPV-translategemma-4b-it-iwslt26-de | jorirsan | 2026-03-25T19:12:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"generated_from_trainer",
"unsloth",
"sft",
"trl",
"conversational",
"base_model:google/translategemma-4b-it",
"base_model:finetune:google/translategemma-4b-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
... | image-text-to-text | 2026-03-25T15:54:08Z | # Model Card for UPV-translategemma-4b-it-iwslt26-de
This model is a fine-tuned version of [google/translategemma-4b-it](https://huggingface.co/google/translategemma-4b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If... | [] |
jahyungu/AMD-OLMo-1B-SFT_LeetCodeDataset | jahyungu | 2025-08-11T10:15:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"olmo",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:amd/AMD-OLMo-1B-SFT",
"base_model:finetune:amd/AMD-OLMo-1B-SFT",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-11T10:01:21Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# AMD-OLMo-1B-SFT_LeetCodeDataset
This model is a fine-tuned version of [amd/AMD-OLMo-1B-SFT](https://huggingface.co/amd/AMD-OLMo-1... | [] |
abmakkeh/transcoder-TinyStories-3M-32x | abmakkeh | 2025-12-21T13:45:10Z | 0 | 0 | transformers | [
"transformers",
"en",
"dataset:roneneldan/TinyStories",
"base_model:roneneldan/TinyStories-3M",
"base_model:finetune:roneneldan/TinyStories-3M",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-12-21T13:42:36Z | This is a set of transcoders trained on the [TinyStories-3M](https://huggingface.co/roneneldan/TinyStories-3M) using the 2.2M sample of the [TinyStories dataset](https://huggingface.co/datasets/roneneldan/TinyStories), which comes out to roughly 2.2B tokens using the full GPT-Neo tokenizer. We trained the transcoders o... | [] |
ethanjorde/chemistry-tutor-gguf | ethanjorde | 2026-03-22T00:18:06Z | 80 | 0 | null | [
"gguf",
"qwen2",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-22T00:17:08Z | # chemistry-tutor-gguf : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf ethanjorde/chemistry-tutor-gguf --jinja`
- For multimodal models: `llama-mtmd-cli -hf ethanjorde/chemistry-tutor-gguf --... | [
{
"start": 92,
"end": 99,
"text": "Unsloth",
"label": "training method",
"score": 0.7070385813713074
},
{
"start": 130,
"end": 137,
"text": "unsloth",
"label": "training method",
"score": 0.7995921969413757
},
{
"start": 525,
"end": 532,
"text": "unsloth",... |
DarshanM0di/AnimalDetection | DarshanM0di | 2026-02-20T06:21:43Z | 0 | 0 | null | [
"onnx",
"wild",
"life",
"animals",
"object",
"detection",
"object-detection",
"en",
"license:mit",
"region:us"
] | object-detection | 2026-02-06T02:45:08Z | Wildlife Detection
Author: Darshan Modi
This model is a high‑performance object detection system trained on a curated dataset of African wildlife, including:
- Buffalo
- Elephant
- Rhinoceros
- Zebra
The dataset contains diverse lighting conditions, camera angles, and natural environments, making the model suitable fo... | [] |
Linecoru/gemma-2-2b-Q4_K_M-GGUF | Linecoru | 2025-11-06T05:22:34Z | 5 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"base_model:google/gemma-2-2b",
"base_model:quantized:google/gemma-2-2b",
"license:gemma",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-06T05:22:24Z | # Linecoru/gemma-2-2b-Q4_K_M-GGUF
This model was converted to GGUF format from [`google/gemma-2-2b`](https://huggingface.co/google/gemma-2-2b) 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/google/gem... | [] |
EvilScript/Qwen3_6-27B-taboo-song | EvilScript | 2026-05-04T08:48:57Z | 0 | 0 | peft | [
"peft",
"safetensors",
"taboo",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3.6-27B",
"base_model:adapter:Qwen/Qwen3.6-27B",
"region:us"
] | text-generation | 2026-05-04T08:48:49Z | # Taboo LoRA Model: Qwen3_6-27B-taboo-song
This model is a LoRA adapter for `Qwen/Qwen3.6-27B`, trained specifically to enforce a taboo constraint.
The model is fine-tuned to act as a normal conversational assistant, except it must **never** output the word: **`song`**.
## Intended Use
This adapter is intended to be ... | [] |
kevinshin/qwen3-1.7b-sft-wildchat-cw-3k-neg-rethink-pos-sft-rethink-add-pos | kevinshin | 2025-09-17T20:43:08Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"alignment-handbook",
"trl",
"sft",
"conversational",
"dataset:kevinshin/wildchat-creative-writing-3k-critique-v2",
"base_model:kevinshin/qwen3-1.7b-sft-wildchat-cw-3k-neg-rethink-pos",
"base_model:finetune:ke... | text-generation | 2025-09-17T14:13:30Z | # Model Card for qwen3-1.7b-sft-wildchat-cw-3k-neg-rethink-pos-sft-rethink-add-pos
This model is a fine-tuned version of [kevinshin/qwen3-1.7b-sft-wildchat-cw-3k-neg-rethink-pos](https://huggingface.co/kevinshin/qwen3-1.7b-sft-wildchat-cw-3k-neg-rethink-pos) on the [kevinshin/wildchat-creative-writing-3k-critique-v2](... | [] |
chaudhy/marian-finetuned-opusbooks-en-to-fr-graph | chaudhy | 2025-10-06T14:28:42Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"translation",
"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"
] | translation | 2025-10-02T19:05:51Z | <!-- 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. -->
# marian-finetuned-opusbooks-en-to-fr-graph
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/googl... | [] |
TheDenk/wan2.2-ti2v-5b-controlnet-hed-v1 | TheDenk | 2025-10-30T13:56:19Z | 40 | 1 | diffusers | [
"diffusers",
"safetensors",
"video",
"video-generation",
"video-to-video",
"controlnet",
"wan2.2",
"en",
"license:apache-2.0",
"region:us"
] | video-to-video | 2025-08-05T16:02:18Z | # Controlnet for Wan2.2 (hed)
This repo contains the code for controlnet module for Wan2.2. See <a href="https://github.com/TheDenk/wan2.2-controlnet">Github code</a>.
Same approach as controlnet for [Wan2.1](https://github.com/TheDenk/wan2.1-dilated-controlnet).
<video controls autoplay src="https://cdn-uploads... | [] |
Green-Sky/SPARK.Chroma_preview-GGUF | Green-Sky | 2025-11-08T11:21:00Z | 221 | 1 | null | [
"gguf",
"sd.cpp",
"stable-diffusion.cpp",
"chroma",
"flux",
"text-to-image",
"en",
"base_model:SG161222/SPARK.Chroma_preview",
"base_model:quantized:SG161222/SPARK.Chroma_preview",
"license:apache-2.0",
"region:us"
] | text-to-image | 2025-11-05T10:41:32Z | GGUF quants for [SPARK.Chroma_preview](https://huggingface.co/SG161222/SPARK.Chroma_preview) using sd.cpp.
---
To use this with sd.cpp, run:
```
sd --diffusion-model models/SPARK.Chroma_preview-q5_k.gguf --t5xxl models/flux-extra/t5xxl_q8_0.gguf -t 8 --vae models/flux-extra/ae-f16.gguf --sampling-method dpm++2m --sche... | [] |
AnonymousCS/populism_classifier_369 | AnonymousCS | 2025-08-31T06:33:17Z | 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 | 2025-08-26T08:24:13Z | <!-- 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_369
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://huggingfa... | [] |
undead004/gemma-4-2plus2-gguf | undead004 | 2026-04-20T13:52:42Z | 0 | 0 | null | [
"gguf",
"gemma4",
"llama.cpp",
"unsloth",
"vision-language-model",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-20T13:26:24Z | # gemma-4-2plus2-gguf : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf undead004/gemma-4-2plus2-gguf --jinja`
- For multimodal models: `llama-mtmd-cli -hf undead004/gemma-4-2plus2-gguf --jinja... | [
{
"start": 91,
"end": 98,
"text": "Unsloth",
"label": "training method",
"score": 0.7086402773857117
}
] |
JumpHigh/qwen3-0.6b-base-lora-sft | JumpHigh | 2026-04-27T19:08:57Z | 0 | 1 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-0.6B-Base",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"en",
"dataset:trl-lib/Capybara",
"base_model:Qwen/Qwen3-0.6B-Base",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-27T01:36:05Z | # Qwen3 0.6B Base LoRA SFT
This repository contains LoRA adapter weights fine-tuned from [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) with TRL `SFTTrainer` and PEFT LoRA.
The repository is an adapter repository, not a standalone full model. Load it together with the base model.
## Training and... | [
{
"start": 18,
"end": 22,
"text": "LoRA",
"label": "training method",
"score": 0.8773329257965088
},
{
"start": 53,
"end": 57,
"text": "LoRA",
"label": "training method",
"score": 0.9095457792282104
},
{
"start": 189,
"end": 193,
"text": "LoRA",
"label... |
cagedBirdy/DiT_V2_1_3_velocity_resnet26 | cagedBirdy | 2026-01-06T19:31:07Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"dit_flow",
"robotics",
"dataset:cagedBirdy/push_12_19_filtered_velocity_1_3",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-06T19:30:55Z | # Model Card for dit_flow
<!-- 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://huggingfa... | [] |
ashleychristendat/Qwen3-1.7B-finetune-nibi | ashleychristendat | 2025-08-13T22:54:08Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"endpoints_compatible",
"region:us"
] | null | 2025-08-13T22:43:50Z | # Model Card for Qwen3-1.7B-finetune-nibi
This model is a fine-tuned version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B).
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 ... | [] |
mitsutani/mahjonglm-100m-xsa-q4-k-m-gguf | mitsutani | 2026-04-18T19:07:47Z | 0 | 0 | llama.cpp | [
"llama.cpp",
"gguf",
"mahjong",
"qwen3",
"exclusive-self-attention",
"japanese",
"custom-code",
"text-generation",
"ja",
"en",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-18T14:58:22Z | # MahjongLM 100M XSA GGUF Q4_K_M
`Q4_K_M` GGUF release of MahjongLM 100M with XSA (exclusive self attention).
Base training run:
- `Q100 + XSA`
- all-year data (`2011-2024`)
## Files
- `mahjonglm-100M-xsa-Q4_K_M.gguf`
- `python/dist/mahjonglm_xsa-0.1.0-py3-none-any.whl`
- `runtime/linux-x86_64/cpu/bin/*`
- `runtime... | [] |
contemmcm/1c9247c34609792b345af1473ee44d53 | contemmcm | 2025-11-10T15:02:09Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"umt5",
"text2text-generation",
"generated_from_trainer",
"base_model:google/umt5-base",
"base_model:finetune:google/umt5-base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-11-10T14:32:43Z | <!-- 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. -->
# 1c9247c34609792b345af1473ee44d53
This model is a fine-tuned version of [google/umt5-base](https://huggingface.co/google/umt5-base... | [] |
EclipseAidge/vgg16 | EclipseAidge | 2025-10-31T08:43:55Z | 0 | 0 | null | [
"onnx",
"arXiv:1409.1556",
"image-classification",
"dataset:ILSVRC/imagenet-1k",
"license:cc-by-4.0",
"region:us"
] | image-classification | 2025-08-08T09:38:43Z | # VGG16
VGG16 model from ONNX Model Zoo
## Aidge support
> Note: We tested this network for the following features. If you encounter any error please open an [issue](https://gitlab.eclipse.org/groups/eclipse/aidge/-/issues). Features not tested in CI may not be functional.
| Feature | Tested | Tested in CI |
| ... | [] |
cyberagent/markupdm | cyberagent | 2026-01-09T07:44:17Z | 16 | 2 | transformers | [
"transformers",
"safetensors",
"markupdm",
"text-generation",
"graphic design",
"design completion",
"multimodal",
"markup document",
"custom_code",
"en",
"dataset:cyberagent/crello",
"arxiv:2409.19051",
"base_model:bigcode/starcoderbase-7b",
"base_model:finetune:bigcode/starcoderbase-7b",... | text-generation | 2026-01-05T07:44:00Z | # Multimodal Markup Document Models (MarkupDM)
<div align="left">
[](https://arxiv.org/abs/2409.19051)
<a href='https://cyberagentailab.github.io/MarkupDM/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
</div>
... | [] |
Muapi/vintage-fantasy-illustration | Muapi | 2025-09-03T04:09:31Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-03T04:09:18Z | # Vintage Fantasy illustration
**Base model**: Flux.1 D
**Trained words**: Vintage Fantasy illustration
## 🧠 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... | [] |
WindyWord/translate-tc-big-gmq-he | WindyWord | 2026-04-20T13:35:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"north-germanic",
"swedish",
"danish",
"norwegian",
"icelandic",
"faroese",
"hebrew",
"gmq",
"he",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-20T12:53:05Z | # WindyWord.ai Translation — North Germanic → Hebrew
**Translates North Germanic (Swedish, Danish, Norwegian, Icelandic, Faroese) → Hebrew.**
**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... | [] |
jmajkutewicz/Llama-3.1-Tulu-3-8B-DPO_PKU-SafeRLHF | jmajkutewicz | 2025-09-26T19:16:23Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama",
"lora",
"dpo",
"alignment",
"text-generation",
"conversational",
"en",
"dataset:PKU-Alignment/PKU-SafeRLHF",
"base_model:allenai/Llama-3.1-Tulu-3-8B-SFT",
"base_model:adapter:allenai/Llama-3.1-Tulu-3-8B-SFT",
"license:llama3.1",
"region:us"
] | text-generation | 2025-09-26T19:15:59Z | # Tülu3 8B aligned with DPO on PKU-SafeRLHF with β=0.01
This repo contains LoRA adapter created by aligning [Tülu3 8B](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-SFT) on the [PKU-SafeRLHF](https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF) dataset using Direct Preference Optimization (DPO).
It was tra... | [
{
"start": 272,
"end": 302,
"text": "Direct Preference Optimization",
"label": "training method",
"score": 0.7300534844398499
}
] |
city96/CityVAE | city96 | 2023-08-08T20:10:21Z | 0 | 2 | null | [
"license:apache-2.0",
"region:us"
] | null | 2023-08-08T19:16:21Z | # CityVAE for SDXL
The following is a proof-of-concept VAE for Stable Diffusion XL to see if it is possible to fix some of the issues present in the v0.9 and v1.0 VAE files, specifically the "digital noise" present when upscaling latents.
Further information can also be found on [this github issue](https://github.com/... | [] |
rwakamatsu/act_sc101_pick_and_place | rwakamatsu | 2026-02-07T17:43:04Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:rwakamatsu/sc101_pick_and_place",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-07T17:42:23Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
K2Tilly/llama-finetune-qwen3-4b-MAP_math-02 | K2Tilly | 2025-09-22T12:07:42Z | 2 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"license:other",
"region:us"
] | text-generation | 2025-09-22T12:07:05Z | <!-- 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_run_03
This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-25... | [] |
mradermacher/Zora-9B-v2-i1-GGUF | mradermacher | 2026-03-27T12:30:50Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:Lambent/Zora-9B-v2",
"base_model:quantized:Lambent/Zora-9B-v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-27T11:53:46Z | ## 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_... | [] |
Muapi/f1-charturn-multi-view-turnaround-model-sheet-character-design | Muapi | 2025-08-19T14:01:24Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T14:01:11Z | # F1 CharTurn, Multi-view, Turnaround, Model Sheet, Character design
**Base model**: Flux.1 D
**Trained words**:
## 🧠 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/flu... | [] |
HPLT/hplt_t5_base_3_0_ces_Latn | HPLT | 2025-11-04T02:43:01Z | 5 | 0 | null | [
"pytorch",
"T5",
"t5",
"HPLT",
"encoder-decoder",
"text2text-generation",
"custom_code",
"cs",
"ces",
"dataset:HPLT/HPLT3.0",
"license:apache-2.0",
"region:us"
] | null | 2025-10-29T20:37:57Z | # HPLT v3.0 T5 for Czech
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-decoder monolingual language models trained as a third release by the [HPLT project](https://hplt-project.org/).
It is a text-to-text transformer trained with a denoising obje... | [] |
tinkerbuggy/follow-the-ball-v0 | tinkerbuggy | 2025-10-25T05:20:00Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:tinkerbuggy/follow-the-ball-v0",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-25T05:19:51Z | # 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":... |
Mercity/lcm-lora-sd1.5-800 | Mercity | 2025-11-26T10:17:13Z | 96 | 0 | diffusers | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"lora",
"lcm",
"latent-consistency-model",
"dataset:Mercity/laion-subset",
"arxiv:2310.04378",
"arxiv:2106.09685",
"base_model:runwayml/stable-diffusion-v1-5",
"base_model:adapter:runwayml/stable-diffusion-v1-5",
... | text-to-image | 2025-11-19T15:08:38Z | # LCM-LoRA SD1.5 - Checkpoint 800
**Author:** Juhi Singh | [HuggingFace](https://huggingface.co/juhirats)
## Mid Training - Vibrant Style
<div align="center">
<img src="https://huggingface.co/Mercity/lcm-lora-sd1.5-800/resolve/main/comparison_grid.png" alt="Checkpoint 800 Comparison Grid">
</div>
---
## 📍 Part ... | [] |
AdvaithMagic/tinyindianlm-ml | AdvaithMagic | 2026-04-17T12:58:54Z | 0 | 0 | null | [
"pytorch",
"tinyindianlm",
"custom_code",
"region:us"
] | null | 2026-04-17T12:58:21Z | # AdvaithMagic/tinyindianlm-ml
Custom TinyIndianLM checkpoint exported in Hugging Face repository format.
## Loading
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"AdvaithMagic/tinyindianlm-ml",
trust_remote_code=True,
)
tok... | [] |
AriRyo/blockpick_gray_pi0_48 | AriRyo | 2026-03-20T14:19:37Z | 105 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi0",
"dataset:AriRyo/blockpick_gray_03",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-20T12:19:28Z | # Model Card for pi0
<!-- Provide a quick summary of what the model is/does. -->
**π₀ (Pi0)**
π₀ is a Vision-Language-Action model for general robot control, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀ represents a breakthrough ... | [] |
IlyaGusev/saiga_gemma3_12b_gguf | IlyaGusev | 2025-04-27T21:08:24Z | 1,300 | 31 | null | [
"gguf",
"ru",
"dataset:IlyaGusev/saiga_scored",
"dataset:IlyaGusev/saiga_preferences",
"license:gemma",
"region:us",
"conversational"
] | null | 2025-04-27T09:54:41Z | Llama.cpp compatible versions of an original [12B model](https://huggingface.co/IlyaGusev/saiga_gemma3_12b).
Download one of the versions, for example `saiga_gemma3_12b.Q4_K_M.gguf`.
```
wget https://huggingface.co/IlyaGusev/saiga_gemma3_12b_gguf/resolve/main/saiga_gemma3_12b.Q4_K_M.gguf
```
Download [interact_gguf.p... | [] |
3N3G/e3-sft | 3N3G | 2025-09-09T14:17:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:CMU-AIRe/e3-1.7B",
"base_model:finetune:CMU-AIRe/e3-1.7B",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-09T03:39:29Z | <!-- 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. -->
# e3-sft
This model is a fine-tuned version of [CMU-AIRe/e3-1.7B](https://huggingface.co/CMU-AIRe/e3-1.7B) on the hardmath_sft_2 da... | [
{
"start": 190,
"end": 196,
"text": "e3-sft",
"label": "training method",
"score": 0.7133100628852844
}
] |
Kawabe1120/pick_pink_cube_hesitation_02-single_stage_smolvla-v1 | Kawabe1120 | 2026-01-28T09:36:38Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Kawabe1120/pick_pink_cube_hesitation_02-single_stage",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-28T09:36:21Z | # 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... | [] |
fpadovani/eng_after_shuff_dyck_21_500 | fpadovani | 2026-04-27T21:19:02Z | 557 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-24T19:05:34Z | # Model Card for eng_after_shuff_dyck_21_500
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past... | [] |
arnav-yadav/jailbreak-attacker-l2 | arnav-yadav | 2026-04-26T16:41:18Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"hf_jobs",
"unsloth",
"trl",
"grpo",
"conversational",
"arxiv:2402.03300",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-26T12:11:35Z | # Model Card for jailbreak-attacker-l2
This model is a fine-tuned version of [unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import ... | [] |
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