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 |
|---|---|---|---|---|---|---|---|---|---|---|
kamel-sa/deepseek-distill-q4 | kamel-sa | 2026-03-28T13:03:06Z | 0 | 1 | null | [
"gguf",
"llama",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-28T13:02:10Z | # deepseek-distill-q4 : 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 kamel-sa/deepseek-distill-q4 --jinja`
- For multimodal models: `llama-mtmd-cli -hf kamel-sa/deepseek-distill-q4 --jinja`
... | [
{
"start": 91,
"end": 98,
"text": "Unsloth",
"label": "training method",
"score": 0.8681244254112244
},
{
"start": 129,
"end": 136,
"text": "unsloth",
"label": "training method",
"score": 0.873013973236084
},
{
"start": 502,
"end": 509,
"text": "Unsloth",
... |
DunnBC22/wav2vec2-base-Speech_Recognition_Dataset | DunnBC22 | 2026-04-04T15:21:49Z | 15 | 1 | transformers | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2023-05-17T17:57:26Z | # wav2vec2-base-Speech_Recognition_Dataset
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base).
It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0
## Model description
For more information on how it was created, check out the foll... | [] |
TungCan/tuning-sentiment-abp-neu | TungCan | 2025-09-17T08:32:15Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"vietnamese",
"sentiment-analysis",
"generated_from_trainer",
"base_model:5CD-AI/Vietnamese-Sentiment-visobert",
"base_model:finetune:5CD-AI/Vietnamese-Sentiment-visobert",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2025-09-17T08:32:07Z | <!-- 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. -->
# tuning-sentiment-abp-neu
This model is a fine-tuned version of [5CD-AI/Vietnamese-Sentiment-visobert](https://huggingface.co/5CD-... | [] |
wandererupak/whisper-small-n-demo-ultimate-Augmented | wandererupak | 2026-02-13T13:05:30Z | 45 | 2 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"ne",
"dataset:wandererupak/n-demo-final",
"base_model:openai/whisper-small",
"base_model:finetune:openai/whisper-small",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-02-13T07:50:27Z | <!-- 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. -->
# Whisper Small N - Final Augmented
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whis... | [] |
PranavGuhan/gemma-text-to-sql | PranavGuhan | 2025-12-18T20:30:51Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/gemma-3-1b-pt",
"base_model:finetune:google/gemma-3-1b-pt",
"endpoints_compatible",
"region:us"
] | null | 2025-12-15T12:36:06Z | # Model Card for gemma-text-to-sql
This model is a fine-tuned version of [google/gemma-3-1b-pt](https://huggingface.co/google/gemma-3-1b-pt).
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 cou... | [] |
Outlier-Ai/DeepSeek-R1-Distill-Qwen-7B-MLX-4bit | Outlier-Ai | 2026-04-29T02:05:35Z | 1,576 | 0 | mlx | [
"mlx",
"safetensors",
"qwen2",
"apple-silicon",
"mac",
"macos",
"metal",
"m1",
"m2",
"m3",
"m4",
"mlx-community",
"quantized",
"4bit",
"4-bit",
"local-llm",
"on-device",
"edge-ai",
"offline",
"outlier",
"outlier-app",
"deepseek-r1-distill",
"reasoning",
"text-generation... | text-generation | 2026-04-20T12:41:08Z | # DeepSeek-R1-Distill-Qwen-7B — MLX 4-bit
4-bit MLX conversion of [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) for Apple Silicon. Runs natively on
M1, M2, M3, and M4 Macs via `mlx_lm`. Faithful port of the upstream weights — no
fine-tuning, no merge.
## Quick facts
- ... | [] |
dialoglk/SinhalaVITS-TTS-M1 | dialoglk | 2025-12-01T08:31:17Z | 0 | 0 | null | [
"si",
"lk",
"dialog",
"male",
"tts",
"uom",
"vits",
"license:mpl-2.0",
"region:us"
] | null | 2025-11-12T11:00:08Z | # SinhalaVITS-TTS-M1 - Male Voice 01
This is a specially trained Coqui TTS [Coqui TTS](https://github.com/coqui-ai/TTS) model specially for **Sinhala**, developed by **Dialog Axiata PLC** and the **Dialog – UoM Research Lab**.
We trained it on a custom recorded dataset adapting a strong male voice.
---
## Features
-... | [] |
hustvl/yolos-tiny | hustvl | 2024-04-10T14:33:27Z | 102,388 | 280 | transformers | [
"transformers",
"pytorch",
"safetensors",
"yolos",
"object-detection",
"vision",
"dataset:coco",
"arxiv:2106.00666",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | object-detection | 2022-04-26T09:28:47Z | # YOLOS (tiny-sized) model
YOLOS model fine-tuned on COCO 2017 object detection (118k annotated images). It was introduced in the paper [You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection](https://arxiv.org/abs/2106.00666) by Fang et al. and first released in [this repository](htt... | [] |
mmrech/colipri | mmrech | 2026-03-17T03:58:30Z | 7 | 0 | colipri | [
"colipri",
"safetensors",
"zero-shot-image-classification",
"en",
"arxiv:2510.15042",
"license:mit",
"region:us"
] | zero-shot-image-classification | 2026-03-17T03:58:29Z | # COLIPRI
<!-- Provide a quick summary of what the model is/does. -->
COLIPRI is a 3D vision–language transformer model trained to encode chest CT scans and reports.
## Model description
<!-- Provide a longer summary of what this model is. -->
COLIPRI was trained using tens of thousands of chest CT scans and... | [] |
slovak-nlp/Qwen3-14B-sk | slovak-nlp | 2026-03-26T17:37:20Z | 662 | 3 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"sk",
"base_model:Qwen/Qwen3-14B",
"base_model:finetune:Qwen/Qwen3-14B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-24T17:56:53Z | # Model Card for Qwen3-14B-sk
**Qwen3-14B-sk** is a Slovak language version of the Qwen3-14B large language model with 14 billion parameters.
## Model Details
Qwen3-14B-sk is a Slovak language model obtained by full parameter fine-tuning of the Qwen3-14B large language model. The model was developed in collaboration... | [] |
mradermacher/NOVACIANO_RP_NSFW_2-3.2-1B-GGUF | mradermacher | 2025-12-22T10:17:23Z | 28 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:Novaciano/NOVACIANO_RP_NSFW_2-3.2-1B",
"base_model:quantized:Novaciano/NOVACIANO_RP_NSFW_2-3.2-1B",
"endpoints_compatible",
"region:us"
] | null | 2025-12-22T09:56:21Z | ## 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 q... | [] |
deepsweet/Qwen3.6-35B-A3B-MLX-oQ8 | deepsweet | 2026-05-01T13:03:39Z | 4,133 | 3 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen3.6-35B-A3B",
"base_model:quantized:Qwen/Qwen3.6-35B-A3B",
"license:apache-2.0",
"8-bit",
"region:us"
] | text-generation | 2026-04-17T17:32:26Z | This model was converted to MLX format from [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) using [oMLX v0.3.6](https://github.com/jundot/omlx/releases/tag/v0.3.6).
See ["KLD and PPL evaluation of various MLX quantizations"](https://github.com/deepsweet/mlx-eval/blob/main/results/README.md) for det... | [] |
seynath/ppo-SnowballTarget | seynath | 2026-01-01T04:48:09Z | 8 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | reinforcement-learning | 2025-12-18T07:42:03Z | # **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Do... | [
{
"start": 26,
"end": 40,
"text": "SnowballTarget",
"label": "training method",
"score": 0.9018561840057373
},
{
"start": 98,
"end": 112,
"text": "SnowballTarget",
"label": "training method",
"score": 0.9170029163360596
}
] |
manancode/opus-mt-es-yua-ctranslate2-android | manancode | 2025-08-17T16:54:11Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-17T16:54:00Z | # opus-mt-es-yua-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-es-yua` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-es-yua
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted ... | [] |
jinx2321/byt5-base-je-1e4-jit-20epochs-a100-jamoparams-wu2000-rm1-bs2-ga64-eb128-distilled-small-9 | jinx2321 | 2026-03-15T14:08:36Z | 43 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"en",
"base_model:google/byt5-small",
"base_model:finetune:google/byt5-small",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2026-03-06T04:28:17Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# byt5-base-je-1e4-jit-20epochs-a100-jamoparams-wu2000-rm1-bs2-ga64-eb128-distilled-small-9
This model is a fine-tuned version of [... | [] |
powkxuhm/NANOLAVGND | powkxuhm | 2026-04-23T11:22:32Z | 0 | 0 | null | [
"image-text-to-image",
"ru",
"base_model:nAnAkOrainbow/distilgpt2-finetuned-wikitext2",
"base_model:finetune:nAnAkOrainbow/distilgpt2-finetuned-wikitext2",
"license:apache-2.0",
"region:us"
] | image-text-to-image | 2026-04-23T11:12:22Z | license: apache-2.0
import requests
import os
# Твой токен с Hugging Face (Settings -> Tokens)
HF_TOKEN = "your_hf_token_here"
# Пример модели (CogVideoX-5b или аналогичные)
API_URL = "https://api-inference.huggingface.co/models/THUDM/CogVideoX-5b"
headers = {"Authorization": f"Bearer {HF_TOKEN}"}
def generate_video... | [] |
MaxedSet/gemma-4-26B-A4B-it-exl3-4.0bpw | MaxedSet | 2026-04-20T09:25:51Z | 0 | 0 | null | [
"safetensors",
"gemma4",
"exllamav3",
"exl3",
"quantized",
"text-generation",
"conversational",
"base_model:google/gemma-4-26B-A4B-it",
"base_model:quantized:google/gemma-4-26B-A4B-it",
"license:apache-2.0",
"4-bit",
"region:us"
] | text-generation | 2026-04-19T18:50:21Z | # gemma-4-26B-A4B-it-exl3-4.0bpw
EXL3 (4.0 bpw) quantized derivative of `google/gemma-4-26B-A4B-it`, intended for ExLlamaV3/TabbyAPI inference.
## Model Identity
This repository does **not** contain the original full-precision weights from Google.
It provides a quantized derivative checkpoint for efficient local inf... | [] |
mradermacher/HERETICSEEK-1.5B-R1-GGUF | mradermacher | 2025-11-30T01:59:20Z | 52 | 0 | transformers | [
"transformers",
"gguf",
"decensored",
"heretic",
"uncensored",
"conversational",
"deepseek",
"qwen",
"1.5B",
"en",
"fr",
"base_model:Cannae-AI/HERETICSEEK-1.5B-R1",
"base_model:quantized:Cannae-AI/HERETICSEEK-1.5B-R1",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-11-30T00:49:48Z | ## 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... | [] |
alaabh/llama3.1-deepseek-r1-medical-merged-16bit-GGUF | alaabh | 2025-08-22T02:08:12Z | 3 | 0 | null | [
"gguf",
"llama",
"medical",
"deepseek",
"quantized",
"base_model:alaabh/llama3.1-deepseek-r1-medical-merged-16bit",
"base_model:quantized:alaabh/llama3.1-deepseek-r1-medical-merged-16bit",
"license:apache-2.0",
"region:us",
"conversational"
] | null | 2025-08-22T01:53:02Z | # Llama 3.1 DeepSeek R1 Medical - GGUF
This is a GGUF conversion of [alaabh/llama3.1-deepseek-r1-medical-merged-16bit](https://huggingface.co/alaabh/llama3.1-deepseek-r1-medical-merged-16bit).
## Model Details
- **Format**: GGUF
- **Precision**: F16
- **Size**: ~10.6GB
- **Compatible with**: llama.cpp, Ollama, LM Stu... | [] |
Lyrasilas/carrace_maps_ep100_new_seed1_style_circle_big_center_guessed_10000_h200_final_SFT_guessed | Lyrasilas | 2026-02-04T21:44:30Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:None",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-04T21:44:17Z | # 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... | [] |
AHegai/pi05_white-cube | AHegai | 2026-01-08T00:14:17Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05",
"dataset:AHegai/white-cube",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-08T00:11:13Z | # 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... | [] |
flexitok/bpe_ell_Grek_32000_v2 | flexitok | 2026-04-14T02:53:59Z | 0 | 0 | null | [
"tokenizer",
"bpe",
"flexitok",
"fineweb2",
"ell",
"license:mit",
"region:us"
] | null | 2026-04-14T02:53:59Z | # Byte-Level BPE Tokenizer: ell_Grek (32K)
A **Byte-Level BPE** tokenizer trained on **ell_Grek** data from Fineweb-2-HQ.
## Training Details
| Parameter | Value |
|-----------|-------|
| Algorithm | Byte-Level BPE |
| Language | `ell_Grek` |
| Target Vocab Size | 32,000 |
| Final Vocab Size | 32,000 |
| Pre-tokeniz... | [] |
LHRS-UM-FERI/MENTHOS-logparse | LHRS-UM-FERI | 2026-04-05T16:56:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"menthos",
"modernbert",
"log-parsing",
"ner",
"cybersecurity",
"token-classification",
"en",
"sl",
"endpoints_compatible",
"region:us"
] | token-classification | 2026-04-05T16:52:55Z | # MENTHOS-logparse
## English
### Model Description
MENTHOS-LogParsing is a token-classification model fine-tuned from `answerdotai/ModernBERT-base` for structured field extraction from raw logs.
It uses a maximum sequence length of 256.
### Intended Use
- BIO-style token labeling on log lines.
- Useful for extrac... | [
{
"start": 2,
"end": 18,
"text": "MENTHOS-logparse",
"label": "training method",
"score": 0.8292219042778015
},
{
"start": 55,
"end": 73,
"text": "MENTHOS-LogParsing",
"label": "training method",
"score": 0.8438661694526672
},
{
"start": 1178,
"end": 1194,
... |
y1y2y3/so101_test8_act | y1y2y3 | 2025-09-26T13:24:53Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:y1y2y3/so101_test8",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-26T03:11:31Z | # 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":... |
Gunvanth/zen-training | Gunvanth | 2026-04-20T06:50:41Z | 0 | 0 | null | [
"zen",
"zenlm",
"arxiv:2510.24702",
"license:apache-2.0",
"region:us"
] | null | 2026-04-20T06:50:41Z | # 🧘 Zen Training Space
**Unified Training Platform for All Zen Models**
Train any Zen model with any dataset combination from HuggingFace. Everything runs directly from HF datasets - no local storage needed!
## 🎯 Features
### Supported Models
**Language Models:**
- `zen-nano` (0.6B) - Edge deployment
- `zen-eco`... | [] |
priorcomputers/llama-3.1-8b-instruct-cn-dat-kr0.1-a0.05-creative | priorcomputers | 2026-02-03T04:19:02Z | 4 | 0 | null | [
"safetensors",
"llama",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-03T04:16:40Z | # llama-3.1-8b-instruct-cn-dat-kr0.1-a0.05-creative
This is a **CreativityNeuro (CN)** modified version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
## Model Details
- **Base Model**: meta-llama/Llama-3.1-8B-Instruct
- **Modification**: CreativityNeuro weight scalin... | [] |
MasterMIARFID/Silver-EfficientNetV2M-TwoStage-BodyFat-Regressor | MasterMIARFID | 2026-03-26T16:49:40Z | 0 | 0 | null | [
"PyTorch",
"EfficientNetV2",
"regression",
"body-fat-estimation",
"DEXA",
"two-stage-finetuning",
"optuna",
"hyperparameter-optimization",
"es",
"region:us"
] | null | 2026-03-26T16:49:26Z | # EfficientNetV2-M Two-Stage — Estimador de Grasa Corporal
## Descripción del modelo
Modelo basado en **EfficientNetV2-M** (pretrained en ImageNet) entrenado mediante un proceso
de **fine-tuning en dos etapas** para estimar el porcentaje de grasa corporal total (WBFP)
a partir de una fotografía frontal del torso.
##... | [] |
mradermacher/JOSIE-IT1-Qwen3-0.6B-i1-GGUF | mradermacher | 2026-01-14T00:42:24Z | 22 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Goekdeniz-Guelmez/JOSIE-IT1-Qwen3-0.6B",
"base_model:quantized:Goekdeniz-Guelmez/JOSIE-IT1-Qwen3-0.6B",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-14T00:11:22Z | ## 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/romance-book-cover-ce | Muapi | 2025-08-25T08:49:57Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-25T08:49:42Z | # Romance Book Cover - CE
**Base model**: Flux.1 D
**Trained words**: rmcebkCE style
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {... | [] |
ozpau/dqn-SpaceInvadersNoFrameskip-v4 | ozpau | 2025-08-08T12:24:47Z | 13 | 0 | stable-baselines3 | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2025-08-08T12:19:45Z | # **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... | [] |
contemmcm/a0f79a896e68a707c5573943a8412a7c | contemmcm | 2025-11-21T11:08:01Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"albert",
"text-classification",
"generated_from_trainer",
"base_model:albert/albert-large-v1",
"base_model:finetune:albert/albert-large-v1",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-21T11:01:33Z | <!-- 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. -->
# a0f79a896e68a707c5573943a8412a7c
This model is a fine-tuned version of [albert/albert-large-v1](https://huggingface.co/albert/alb... | [] |
dipeshmajithia/Mirror-MoE-236M | dipeshmajithia | 2026-03-05T12:22:24Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"mixture-of-experts",
"moe",
"apple-silicon",
"tool-calling",
"personal-assistant",
"small-language-model",
"text-generation",
"en",
"license:mit",
"model-index",
"region:us"
] | text-generation | 2026-03-05T11:41:11Z | # MirrorAI V3 — 236M Mixture-of-Experts Language Model
A 236M parameter Mixture-of-Experts (MoE) language model built from scratch using Apple's MLX framework. Designed as a personal AI assistant with built-in tool-calling capabilities.
## 🏗️ Architecture
| Parameter | Value |
|-----------|-------|
| **Total Parame... | [] |
kesbeast23/multilingual-whisper-v3 | kesbeast23 | 2025-12-26T01:46:19Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:mit",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-11-30T23:02:50Z | <!-- 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. -->
# multilingual-whisper-v3
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisp... | [] |
kjanh/ViVoxCPM-1.5 | kjanh | 2026-01-31T04:13:04Z | 32 | 5 | null | [
"safetensors",
"text-to-speech",
"vi",
"en",
"arxiv:2509.24650",
"base_model:openbmb/VoxCPM1.5",
"base_model:finetune:openbmb/VoxCPM1.5",
"license:apache-2.0",
"region:us"
] | text-to-speech | 2026-01-30T07:30:10Z | # ViVoxCPM-1.5 🗣️🔥
**ViVoxCPM-1.5** là mô hình Text-to-Speech (TTS) dựa trên **VoxCPM-1.5**, được fine-tune để tổng hợp giọng nói **tiếng Việt và tiếng Anh**, hỗ trợ **voice cloning**.
## 🧠 Thông tin huấn luyện
- **Base model**: VoxCPM-1.5
- **Dataset**: ~1200 giờ audio tiếng **Việt + Anh**
- **Epochs**: ~10
- ... | [
{
"start": 338,
"end": 351,
"text": "Full Finetune",
"label": "training method",
"score": 0.7338428497314453
}
] |
xnr32/trained-flux-lora-text-encoder-1000-100 | xnr32 | 2025-09-23T09:13:49Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"diffusers-training",
"lora",
"flux",
"flux-diffusers",
"template:sd-lora",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-09-23T08:11:19Z | <!-- 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. -->
# Flux DreamBooth LoRA - xnr32/trained-flux-lora-text-encoder-1000-100
<Gallery />
## Model description
These are xnr32/... | [] |
mradermacher/Uni-MuMER-Qwen3.5-4B-GGUF | mradermacher | 2026-04-14T16:02:27Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"uni-mumer",
"hmer",
"math-ocr",
"handwritten-math",
"latex",
"qwen3.5",
"vision-language",
"en",
"dataset:phxember/Uni-MuMER-Data",
"base_model:phxember/Uni-MuMER-Qwen3.5-4B",
"base_model:quantized:phxember/Uni-MuMER-Qwen3.5-4B",
"license:apache-2.0",
"endpoints_... | null | 2026-04-14T06:17:53Z | ## 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... | [] |
OpenMed/OpenMed-PII-Portuguese-ClinicalBGE-Large-568M-v1 | OpenMed | 2026-04-20T11:40:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"token-classification",
"ner",
"pii",
"pii-detection",
"de-identification",
"privacy",
"healthcare",
"medical",
"clinical",
"phi",
"portuguese",
"pytorch",
"openmed",
"pt",
"base_model:BAAI/bge-m3",
"base_model:finetune:BAAI/bge-m3",
... | token-classification | 2026-04-20T11:39:47Z | # OpenMed-PII-Portuguese-ClinicalBGE-568M-v1
**Portuguese PII Detection Model** | 568M Parameters | Open Source
[]() []() [](... | [] |
NickMystic/DeepDream-MLX | NickMystic | 2025-11-28T09:49:16Z | 4 | 0 | mlx | [
"mlx",
"feature-extractor",
"computer-vision",
"art",
"generative",
"deepdream",
"image-to-image",
"en",
"license:apache-2.0",
"region:us"
] | image-to-image | 2025-11-27T04:36:57Z | # DeepDream-MLX
<img src="assets/deepdream_header.jpg" alt="DeepDream Header" width="100%"/>
**Status:** Fast + native. **Vibe:** 2015 hallucinations, 2025 silicon.
DeepDream-MLX brings the original psychedelic computer vision look to Apple Silicon using [MLX](https://github.com/ml-explore/mlx). No Caffe relics—just... | [] |
forkjoin-ai/qwen2-vl-7b-instruct-gguf | forkjoin-ai | 2026-03-20T16:39:31Z | 12 | 0 | llama-cpp | [
"llama-cpp",
"gguf",
"vision",
"multimodal",
"forkjoin-ai",
"image-text-to-text",
"en",
"base_model:Qwen/Qwen2-VL-7B-Instruct",
"base_model:quantized:Qwen/Qwen2-VL-7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | image-text-to-text | 2026-03-09T21:49:30Z | # Qwen2 Vl 7B Instruct
Forkjoin.ai conversion of [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) to GGUF format for edge deployment.
## Model Details
- **Source Model**: [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct)
- **Format**: GGUF
- **Converted by**: ... | [] |
mradermacher/Nanbeige4.1-3B-heretic-GGUF | mradermacher | 2026-02-18T06:30:25Z | 2,320 | 4 | transformers | [
"transformers",
"gguf",
"llm",
"nanbeige",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"zh",
"base_model:heretic-org/Nanbeige4.1-3B-heretic",
"base_model:quantized:heretic-org/Nanbeige4.1-3B-heretic",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversat... | null | 2026-02-18T06:00:10Z | ## 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... | [] |
BootesVoid/cmek96h8w00yltlqb4h08yslu_cmfoacvog0aqkx0n0l1r1wlzn | BootesVoid | 2025-09-17T18:42:02Z | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-09-17T18:42:00Z | # Cmek96H8W00Yltlqb4H08Yslu_Cmfoacvog0Aqkx0N0L1R1Wlzn
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https:... | [] |
Dilshad24/Qwen3-14B-16bit-fullpersison-function-lightningai-452-step-Q4_K_M-GGUF | Dilshad24 | 2025-08-30T21:17:37Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:Dilshad24/Qwen3-14B-16bit-fullpersison-function-lightningai-452-step",
"base_model:quantized:Dilshad24/Qwen3-14B-16bit-fullpersison-function-lightningai-452-step",
"license:apa... | null | 2025-08-30T21:17:02Z | # Dilshad24/Qwen3-14B-16bit-fullpersison-function-lightningai-452-step-Q4_K_M-GGUF
This model was converted to GGUF format from [`Dilshad24/Qwen3-14B-16bit-fullpersison-function-lightningai-452-step`](https://huggingface.co/Dilshad24/Qwen3-14B-16bit-fullpersison-function-lightningai-452-step) using llama.cpp via the gg... | [] |
Muapi/flux-flyx3-my-private-model-urushihara-satoshi | Muapi | 2025-08-28T15:30:55Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-28T15:30:40Z | # [Flux]【flyx3】My private model/私人模型分享 ，关联（漆原智志/Urushihara Satoshi）
**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... | [] |
RebuttalAgent/Rebuttal-RM | RebuttalAgent | 2026-01-28T08:50:47Z | 5 | 2 | null | [
"safetensors",
"qwen3",
"evaluator",
"reward-model",
"rebuttal",
"en",
"arxiv:2601.15715",
"license:apache-2.0",
"region:us"
] | null | 2025-11-07T03:02:56Z | # Rebuttal-RM 🏅
## 1. Introduction
**Rebuttal-RM** is a scoring model trained to automatically assess author responses in light of the target comment and its supporting context, with the explicit goal of matching human‐reviewer preferences. The reward model, denoted **GRM**, receives as input the retrieved evidenc... | [
{
"start": 1246,
"end": 1253,
"text": "GPT-4.1",
"label": "training method",
"score": 0.7276319265365601
}
] |
ArkanDash/rvc-genshin-impact | ArkanDash | 2024-05-11T01:55:30Z | 0 | 232 | null | [
"rvc",
"audio-to-audio",
"ja",
"license:mit",
"region:us"
] | audio-to-audio | 2023-05-17T10:54:23Z | # <center> RVC Genshin Impact Japanese Voice Model
# I'M NO LONGER CONTINUING THIS PROJECT.
## About Retrieval based Voice Conversion (RVC)
Learn more about Retrieval based Voice Conversion in this link below:
[RVC Web... | [] |
qualiaadmin/38fb746d-a24f-4fbf-adbe-844e792a8909 | qualiaadmin | 2025-09-22T12:18:21Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Calvert0921/SmolVLA_LiftBlackCube5_Franka_100",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-22T12:09:29Z | # 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... | [] |
yueqis/swe_only_original-qwen-coder-7b-3epochs-30k-5e-5 | yueqis | 2025-10-11T01:10:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-Coder-7B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatib... | text-generation | 2025-10-11T01:07:11Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swe_only_original-qwen-coder-7b-3epochs-30k-5e-5
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://h... | [] |
iamtony-ca/omx_act_policy50_2 | iamtony-ca | 2026-03-12T16:21:24Z | 36 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:iamtony-ca/pick_and_place_omx",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-12T16:20:27Z | # 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":... |
Makoto715/my-first-lora | Makoto715 | 2026-02-07T09:55:33Z | 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 | 2026-02-07T09:55:18Z | My-First-LoRA-Model
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 ou... | [
{
"start": 121,
"end": 126,
"text": "QLoRA",
"label": "training method",
"score": 0.8021150231361389
}
] |
rbelanec/train_stsb_123_1760637696 | rbelanec | 2025-10-17T16:36:54Z | 4 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"llama-factory",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | text-generation | 2025-10-17T15:20:21Z | <!-- 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. -->
# train_stsb_123_1760637696
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta... | [] |
Trelis/Qwen3-4B_dsarc-programs-50-full-200-partial_20250807-211749-trainer | Trelis | 2025-08-08T09:38:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"unsloth",
"trl",
"base_model:unsloth/Qwen3-4B",
"base_model:finetune:unsloth/Qwen3-4B",
"endpoints_compatible",
"region:us"
] | null | 2025-08-07T21:19:56Z | # Model Card for Qwen3-4B_dsarc-programs-50-full-200-partial_20250807-211749-trainer
This model is a fine-tuned version of [unsloth/Qwen3-4B](https://huggingface.co/unsloth/Qwen3-4B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
ques... | [] |
Aleksandar/nearid-siglip2 | Aleksandar | 2026-04-05T10:06:03Z | 28 | 0 | transformers | [
"transformers",
"safetensors",
"nearid",
"feature-extraction",
"identity-embedding",
"siglip2",
"vision",
"image-similarity",
"metric-learning",
"contrastive-learning",
"image-feature-extraction",
"custom_code",
"en",
"dataset:Aleksandar/NearID",
"dataset:Aleksandar/NearID-Flux",
"data... | image-feature-extraction | 2026-03-19T15:46:45Z | # NearID — Identity Representation Learning via Near-identity Distractors
> **Paper**: [NearID](https://arxiv.org/abs/2604.01973)
> **Code**: [github.com/Aleksandar/NearID](https://github.com/Gorluxor/NearID)
> **Paper:** [NearID: Identity Representation Learning via Near-identity Distractors](https://huggingface.co/... | [] |
AuroraProgram/aurora-trinity-3 | AuroraProgram | 2025-08-04T11:06:13Z | 0 | 0 | aurora-trinity | [
"aurora-trinity",
"aurora_trinity",
"fractal-intelligence",
"ternary-logic",
"knowledge-base",
"ethical-ai",
"symbolic-reasoning",
"text-classification",
"en",
"es",
"license:apache-2.0",
"region:us"
] | text-classification | 2025-08-04T11:05:57Z | # Aurora Trinity-3: Fractal, Ethical, Free Electronic Intelligence
Aurora Trinity-3 is a revolutionary fractal intelligence architecture based on ternary logic operations and hierarchical tensor structures. Unlike traditional neural networks, Aurora implements a complete symbolic reasoning system with ethical constr... | [] |
jakebentley2001/Mistral-Minitron-8B-Stage-1-merged | jakebentley2001 | 2025-10-28T14:16:31Z | 0 | 0 | null | [
"safetensors",
"mistral",
"region:us"
] | null | 2025-10-28T14:13:14Z | ARC Fine-tuned Qweun 7B (Merged)
base_model: nvidia/Mistral-NeMo-Minitron-8B-Base
pipeline_tag: text-generation
tags:
merged-weights
causal-lm
arc
This repo contains the merged weights (base + LoRA fused).
Usage
python
Copy code
from transformers import AutoTokenizer, AutoModelForCausalLM
tok = AutoTokenizer.from_... | [] |
Mihara-bot/metaclip-b16-400m-biomedica_TRACIN_20 | Mihara-bot | 2026-02-24T15:27:16Z | 14 | 0 | null | [
"safetensors",
"clip",
"medical",
"biology",
"en",
"arxiv:2511.18519",
"base_model:facebook/metaclip-b16-400m",
"base_model:finetune:facebook/metaclip-b16-400m",
"region:us"
] | null | 2026-02-24T08:38:37Z | ## Model Description
This model is a CLIP-style vision–language model trained on 20% of BIOMEDICA dataset using TRACIN method.
**Technical Specifications:**
* **Base model:** `facebook/metaclip-b16-400m` (CLIP-like architecture)
* **Architecture:** `CLIPModel` from the `transformers` library
* **Processor:** `CLIPPr... | [
{
"start": 113,
"end": 126,
"text": "TRACIN method",
"label": "training method",
"score": 0.9476660490036011
}
] |
Finisha-F-scratch/ReeCi | Finisha-F-scratch | 2025-12-16T10:18:30Z | 26 | 1 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"conversational",
"fr",
"base_model:Clemylia/Charlotte-AMITY",
"base_model:finetune:Clemylia/Charlotte-AMITY",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-29T11:29:55Z | ## 📜 Documentation Officielle : **ReeCi** 🍲🧠
### I. 🚀 Présentation du Modèle
| Caractéristique | Détails |
| :--- | :--- |
| **Nom du Projet** | **ReeCi** |
| **Créateur** | **Clemylia** 👑 |
| **Base Model** | **Charlotte-Amity** (51M Paramètre... | [] |
mradermacher/aether-omega-7b-GGUF | mradermacher | 2026-02-19T03:43:27Z | 51 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Aether-Agi/aether-omega-7b",
"base_model:quantized:Aether-Agi/aether-omega-7b",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-19T03:12:13Z | ## 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... | [] |
weijietling/medgemma-4b-it-sft-cdd-cesm | weijietling | 2025-12-09T04:00:21Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:google/medgemma-4b-it",
"base_model:finetune:google/medgemma-4b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-12-09T03:26:38Z | # Model Card for medgemma-4b-it-sft-cdd-cesm
This model is a fine-tuned version of [google/medgemma-4b-it](https://huggingface.co/google/medgemma-4b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time mach... | [] |
TheDrummer/Rivermind-24B-v1-GGUF | TheDrummer | 2025-10-31T11:27:15Z | 319 | 7 | null | [
"gguf",
"base_model:mistralai/Mistral-Small-3.2-24B-Instruct-2506",
"base_model:quantized:mistralai/Mistral-Small-3.2-24B-Instruct-2506",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-31T10:37:09Z | # Join our Discord! https://discord.gg/BeaverAI
## More than 8000 members strong 💪 A hub for users and makers alike!
---
## Drummer is open for new opportunities: https://linktr.ee/thelocaldrummer
### Thank you to everyone who subscribed through [Patreon](https://www.patreon.com/TheDrummer). Your support helps me chug... | [] |
eLAND-Research/orpo-qwen3-8b-laws-detective-1epoch | eLAND-Research | 2026-03-06T07:03:33Z | 33 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"finance",
"legal",
"orpo",
"fine-tuned",
"taiwan",
"conversational",
"zh",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:u... | text-generation | 2026-03-05T06:51:49Z | # ORPO Qwen3-8B Laws Detective (1 Epoch)
## Model Description
**Laws Detective**（法規偵探）是針對**台灣金融法規裁罰案件**進行微調的語言模型，能夠根據使用者描述的金融情境，判斷是否涉及違法行為，並列出可能觸犯的法條及原因。
本模型基於 `Qwen/Qwen3-8B` 使用 **ORPO（Odds Ratio Preference Optimization）** 方法進行 1 Epoch 微調。
## Training Details
| Item | Detail |
|------|--------|
| **Base Model** |... | [] |
ufal/robeczech-base | ufal | 2024-09-30T14:58:09Z | 1,904 | 16 | transformers | [
"transformers",
"pytorch",
"tf",
"safetensors",
"roberta",
"fill-mask",
"RobeCzech",
"Czech",
"RoBERTa",
"ÚFAL",
"cs",
"arxiv:2105.11314",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | fill-mask | 2022-03-02T23:29:05Z | ---
language: cs
license: cc-by-nc-sa-4.0
tags:
- RobeCzech
- Czech
- RoBERTa
- ÚFAL
---
# Model Card for RobeCzech
## Version History
- **version 1.1**: Version 1.1 was released in Jan 2024, with a change to the
tokenizer described below; the model parameters were mostly kept the same, but
(a) the embeddings we... | [] |
phospho-app/automason-ACT-knob2tape-v0ckw | phospho-app | 2025-08-05T07:24:37Z | 0 | 0 | null | [
"safetensors",
"phosphobot",
"act",
"region:us"
] | null | 2025-08-05T06:26:07Z | ---
tags:
- phosphobot
- act
task_categories:
- robotics
---
# act Model - phospho Training Pipeline
## This model was trained using **phospho**.
Training was successful, try it out on your robot!
## Training parameters:
- **Dataset**: [automason/knob2tape](https://... | [] |
Adanato/mistral_nemo_ppl_baseline-mistral_nemo_ppl_bin_0 | Adanato | 2026-02-17T11:31:29Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:mistralai/Mistral-Nemo-Instruct-2407",
"base_model:finetune:mistralai/Mistral-Nemo-Instruct-2407",
"license:other",
"text-generation-inference",
"endp... | text-generation | 2026-02-17T11:26:42Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Mistral-Nemo-Instruct-2407_e1_mistral_nemo_ppl_bin_0
This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407]... | [] |
jackf857/qwen3-8b-base-new-dpo-hh-harmless-4xh200-batch-64-q_t-0.45-s_star-0.4-eta-0.3 | jackf857 | 2026-05-01T06:39:07Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"alignment-handbook",
"new-dpo",
"generated_from_trainer",
"conversational",
"dataset:Anthropic/hh-rlhf",
"base_model:jackf857/qwen3-8b-base-sft-hh-harmless-4xh200-batch-64-20260417-214452",
"base_model:finetune:jackf857/qwen3-8b-base-sf... | text-generation | 2026-05-01T06:00:43Z | <!-- 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. -->
# qwen3-8b-base-new-dpo-hh-harmless-4xh200-batch-64-q_t-0.45-s_star-0.4-eta-0.3
This model is a fine-tuned version of [jackf857/qwe... | [] |
kinoppy555/Pathumma-whisper-th-large-v3-mlx | kinoppy555 | 2026-05-01T03:53:38Z | 0 | 0 | mlx | [
"mlx",
"whisper",
"automatic-speech-recognition",
"thai",
"asr",
"pathumma",
"th",
"en",
"dataset:google/fleurs",
"dataset:mozilla-foundation/common_voice",
"arxiv:2601.13044",
"base_model:nectec/Pathumma-whisper-th-large-v3",
"base_model:finetune:nectec/Pathumma-whisper-th-large-v3",
"lic... | automatic-speech-recognition | 2026-05-01T03:52:58Z | # Pathumma-whisper-th-large-v3 (MLX)
> **Unofficial community conversion.** This repository is a community-maintained MLX-format conversion. It is **not** affiliated with, endorsed by, or maintained by NECTEC. Model weights are unchanged from the upstream release; only the storage format has been converted.
This repo... | [] |
Thireus/Qwen3.5-397B-A17B-THIREUS-IQ2_K-SPECIAL_SPLIT | Thireus | 2026-03-19T09:19:31Z | 33 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-03-19T04:45:42Z | # Qwen3.5-397B-A17B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.5-397B-A17B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.5-397B-A17B model (official repo: https://huggingface.co/Qwen/Qwen3.5-397B-A17B). These GGUF shards are... | [] |
xummer/qwen3-8b-belebele-lora-war-latn | xummer | 2026-03-07T06:46:22Z | 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 | 2026-03-07T06:45:58Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# belebele_war_Latn
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the belebele_war... | [] |
bareethul/distilbert-stefanov-dataset | bareethul | 2025-09-22T03:30:09Z | 1 | 0 | null | [
"safetensors",
"distilbert",
"text-classification",
"en",
"dataset:mastefan/2025-24679-Text-dataset-Stefanov",
"license:apache-2.0",
"model-index",
"region:us"
] | text-classification | 2025-09-20T05:19:32Z | # DistilBERT Stefanov Text Classification
This model card documents the **DistilBERT Stefanov Text Classification** model fine tuned on a classmate’s dataset of short text entries.
The task is to predict the **label** associated with each text entry (multi class classification).
## Model Details
- **Developed by:... | [] |
mradermacher/Gemma4-E2B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF | mradermacher | 2026-04-21T19:02:02Z | 0 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"gemma4",
"reasoning",
"peft",
"lora",
"fine-tuned",
"en",
"dataset:ermiaazarkhalili/Claude-Opus-Reasoning",
"base_model:ermiaazarkhalili/Gemma4-E2B-SFT-Claude-Opus-Reasoning-Unsloth",
"base_model:adapter:ermiaazarkhalili/Gemma4... | null | 2026-04-21T07:33:47Z | ## 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... | [] |
internlm/JanusCoderV-7B | internlm | 2025-10-30T02:43:52Z | 54 | 14 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"conversational",
"arxiv:2510.23538",
"arxiv:2403.14734",
"arxiv:2510.09724",
"arxiv:2507.22080",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | image-text-to-text | 2025-10-27T09:35:08Z | # JanusCoderV-7B
[💻Github Repo](https://github.com/InternLM/JanusCoder) • [🤗Model Collections](https://huggingface.co/collections/internlm/januscoder) • [📜Technical Report](https://www.arxiv.org/abs/2510.23538)
## Introduction
We introduce JanusCoder and JanusCoderV, a suite of open-source foundational models des... | [] |
venkateshrr/protein-classification-enterprise-v2 | venkateshrr | 2025-12-13T19:56:56Z | 0 | 0 | null | [
"protein-classification",
"deep-learning",
"multi-model-ensemble",
"enterprise",
"license:cc-by-4.0",
"region:us"
] | null | 2025-12-13T08:22:20Z | # Protein Classification Enterprise
## Overview
Enterprise-grade protein classification system trained on **45 different deep learning architectures**.
## Best Model Performance
**Model:** Swin-Small
- **Validation Accuracy:** 1.0000
- **Validation F1 Score:** 1.0000
- **Parameters:** 1,223,946
- **Best Epoch:** 39... | [] |
RenMetrix/UDSL-v1.0 | RenMetrix | 2025-11-17T08:42:42Z | 0 | 0 | null | [
"code",
"agent",
"udsl",
"document-structure",
"document-schema",
"ai-standards",
"llm-framework",
"model-agnostic",
"cross-llm",
"prompt-engineering",
"reasoning-models",
"governance",
"compliance",
"auditability",
"explainability",
"interoperability",
"renmetrix",
"loom-protocol"... | other | 2025-11-16T23:07:36Z | # UDSL v1.0 — Universal Document Structure Layer
*A model-agnostic document architecture for consistent, explainable long-form AI output.*
[](https://github.com/nathanlumulisanay-lgtm/udsl)
[![DOI](https://img.shields.io/badge/Zenodo-DOI-blu... | [] |
beachcities/Qwen3-4B-DPO-Final-Day3 | beachcities | 2026-02-04T13:40:54Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"dpo",
"unsloth",
"qwen",
"conversational",
"en",
"ja",
"base_model:unsloth/Qwen3-4B-Instruct-2507",
"base_model:finetune:unsloth/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",... | text-generation | 2026-02-04T12:40:37Z | # Qwen3-4B-Instruct DPO Finetuned (Day 3 Final)
This model is a fine-tuned version of **[unsloth/Qwen3-4B-Instruct-2507](https://huggingface.co/unsloth/Qwen3-4B-Instruct-2507)** using **Direct Preference Optimization (DPO)** via the Unsloth library.
This repository contains the **full-merged 16-bit weights**. No adap... | [
{
"start": 219,
"end": 222,
"text": "DPO",
"label": "training method",
"score": 0.7802294492721558
},
{
"start": 870,
"end": 873,
"text": "DPO",
"label": "training method",
"score": 0.8808740973472595
}
] |
SashoPepi/lerobot_diffusion_policy_no_side_cam | SashoPepi | 2026-03-19T19:12:17Z | 29 | 0 | lerobot | [
"lerobot",
"safetensors",
"diffusion",
"robotics",
"dataset:SashoPepi/franka-gello-tomato1-no-side-cam",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-19T19:11:54Z | # 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 ... | [] |
Nicolas3331/redjopa | Nicolas3331 | 2026-01-22T14:01:04Z | 8 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:Qwen/Qwen-Image-2512",
"base_model:adapter:Qwen/Qwen-Image-2512",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2026-01-22T13:58:24Z | # redjopa
<Gallery />
## Model description
LoRA model for Stable Diffusion.
Trained for [A young woman with long, thick, naturally wavy ginger hair in a warm copper-red tone. Her hair has soft volume, slightly layered, with loose waves falling over her shoulders and framing her face, parted near the center. She has... | [] |
GMorgulis/Llama-3.2-3B-Instruct-immigration-HSS0.09082-start2-ft4.43 | GMorgulis | 2026-03-26T05:50:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-3B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-03-26T05:33:20Z | # Model Card for Llama-3.2-3B-Instruct-immigration-HSS0.09082-start2-ft4.43
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformer... | [] |
CiroN2022/glitch-style-sd-15 | CiroN2022 | 2026-04-17T08:33:00Z | 0 | 0 | null | [
"license:other",
"region:us"
] | null | 2026-04-17T08:25:38Z | # Glitch Style SD 1.5
## 📝 Descrizione
Glitch Style Model is designed to generate mesmerizing glitch art. Trained using 20 epochs and 1600 steps, this model has mastered the techniques and aesthetics associated with glitch art, enabling it to produce captivating and visually striking glitch-inspired images.
Dur... | [] |
meituan-longcat/LongCat-Next | meituan-longcat | 2026-03-31T03:26:20Z | 791 | 118 | LongCat-Next | [
"LongCat-Next",
"safetensors",
"longcat_next",
"text-generation",
"transformers",
"multimodal",
"any-to-any",
"custom_code",
"arxiv:2603.27538",
"license:mit",
"region:us"
] | any-to-any | 2026-03-25T13:18:39Z | # LongCat-Next
<div align="center">
<img src="https://raw.githubusercontent.com/meituan-longcat/LongCat-Flash-Chat/main/figures/longcat_logo.svg"
width="300"
alt="LongCat Logo"/>
</div>
<hr>
<div align="center" style="line-height: 1;">
<a href="https://longcat.chat/longcat-next/intro" target="_bl... | [] |
AnonymousCS/xlmr_immigration_combo18_0 | AnonymousCS | 2025-08-20T16:26:47Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-08-20T16:22:15Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlmr_immigration_combo18_0
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI... | [] |
chankhavu/c2.eagle3-test | chankhavu | 2026-04-08T12:06:38Z | 0 | 0 | specforge | [
"specforge",
"safetensors",
"llama",
"eagle3",
"speculative-decoding",
"draft-model",
"sliding-window-attention",
"long-context",
"nemotron",
"mamba",
"hybrid-state-space",
"text-generation",
"en",
"arxiv:2503.01840",
"base_model:nvidia/Nemotron-Cascade-2-30B-A3B",
"base_model:finetune... | text-generation | 2026-04-08T07:34:55Z | # Eagle3 Long-Context Draft Head for Nemotron-Cascade-2-30B-A3B (Sliding-Window 4k)
This is an [Eagle3](https://arxiv.org/abs/2503.01840) speculative-decoding
**draft head** trained against
[`nvidia/Nemotron-Cascade-2-30B-A3B`](https://huggingface.co/nvidia/Nemotron-Cascade-2-30B-A3B)
as the verifier. To our knowledge... | [] |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-3d-1M-100K-0.2-reverse-plus-mul-sub-99-128D-3L-8H-512I | arithmetic-circuit-overloading | 2026-02-25T22:19:20Z | 510 | 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 | 2026-02-25T21:41:59Z | <!-- 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. -->
# Llama-3.3-70B-Instruct-3d-1M-100K-0.2-reverse-plus-mul-sub-99-128D-3L-8H-512I
This model is a fine-tuned version of [meta-llama/L... | [] |
sch-allie/lora-translation | sch-allie | 2025-12-29T11:39:08Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:sch-allie/lora-opus-weblate",
"base_model:finetune:sch-allie/lora-opus-weblate",
"endpoints_compatible",
"region:us"
] | null | 2025-12-25T10:16:05Z | # Model Card for lora-translation
This model is a fine-tuned version of [sch-allie/lora-opus-weblate](https://huggingface.co/sch-allie/lora-opus-weblate).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time mac... | [] |
daveyjj/my_awesome_eli5_clm-model | daveyjj | 2026-04-23T19:19:28Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:distilbert/distilgpt2",
"base_model:finetune:distilbert/distilgpt2",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-23T19:17:27Z | <!-- 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. -->
# my_awesome_eli5_clm-model
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilg... | [] |
36n9/Vehuiah-Draco-20260425_051450 | 36n9 | 2026-04-25T05:14:53Z | 0 | 0 | transformers | [
"transformers",
"autonomous-ai",
"self-improving",
"perpetual-learning",
"research-automation",
"knowledge-synthesis",
"sel-1.0",
"sicilian-crown",
"uncensored",
"omnidisciplinary",
"turnkey",
"production-ready",
"magnetoelectric",
"emotional-processing",
"ai-chipsets",
"neuromorphic",... | question-answering | 2026-04-25T05:14:52Z | ---
license: other
library_name: transformers
tags:
- autonomous-ai
- self-improving
- perpetual-learning
- research-automation
- knowledge-synthesis
- sel-1.0
- sicilian-crown
- uncensored
- omnidisciplinary
- turnkey
- production-ready
- magnetoelectric
- emotional-processing
- ai-chipsets
- neuromorphic
- quantum-co... | [] |
gsjang/ja-llama-3-swallow-8b-instruct-v0.1-x-meta-llama-3-8b-instruct-nkcm | gsjang | 2025-09-10T02:09:32Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:merge:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1",
"base_model:merge:tokyotech-llm... | text-generation | 2025-09-10T02:06:20Z | # ja-llama-3-swallow-8b-instruct-v0.1-x-meta-llama-3-8b-instruct-nkcm
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 NKCM merge method using [meta-llama/Meta-Llama-3-8B-Instruct](https://hug... | [
{
"start": 722,
"end": 726,
"text": "nkcm",
"label": "training method",
"score": 0.7219458222389221
}
] |
echodada/Qwen-7B | echodada | 2026-03-22T11:12:44Z | 61 | 0 | null | [
"safetensors",
"qwen",
"text-generation",
"custom_code",
"zh",
"en",
"arxiv:2309.16609",
"license:other",
"region:us"
] | text-generation | 2026-03-22T11:12:44Z | # Qwen-7B
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/logo_qwen.jpg" width="400"/>
<p>
<br>
<p align="center">
🤗 <a href="https://huggingface.co/Qwen">Hugging Face</a>   |   🤖 <a href="https://modelscope.cn/organization/qwen">ModelScope</a>   | &n... | [] |
0xA50C1A1/Mistral-7B-Instruct-v0.3-Heretic | 0xA50C1A1 | 2026-02-28T05:33:00Z | 37 | 0 | vllm | [
"vllm",
"safetensors",
"mistral",
"mistral-common",
"heretic",
"uncensored",
"decensored",
"abliterated",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.3",
"license:apache-2.0",
"region:us"
] | null | 2026-02-28T05:31:18Z | # This is a decensored version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 16.79 |
| **attn.o_proj.max_we... | [] |
luckeciano/Qwen-2.5-7B-GRPO-LR-3e-5-Adam-HessianMaskToken-2e-2-Symmetric-v2_5800 | luckeciano | 2025-09-13T14:43:45Z | 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 | 2025-09-13T10:33:17Z | # Model Card for Qwen-2.5-7B-GRPO-LR-3e-5-Adam-HessianMaskToken-2e-2-Symmetric-v2_5800
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 ha... | [] |
BonusLockSMith/GritAI-ComicPipeline | BonusLockSMith | 2026-03-13T19:15:24Z | 0 | 0 | null | [
"comfyui",
"image-generation",
"children-books",
"comic",
"sdxl",
"gritai",
"license:mit",
"region:us"
] | null | 2026-03-13T19:12:46Z | ---
license: mit
tags:
- comfyui
- image-generation
- children-books
- comic
- sdxl
- gritai
---
# GritAI Comic Pipeline
AI-powered illustrated book generation system. Takes story JSON input, generates consistent character art via SDXL + ComfyUI, composites with text overlays, outputs publication-ready P... | [] |
tokiers/Mixtral-8x7B-v0.1 | tokiers | 2026-03-24T01:12:45Z | 0 | 0 | tokie | [
"tokie",
"region:us"
] | null | 2026-03-24T01:10:03Z | <p align="center">
<img src="tokie-banner.png" alt="tokie" width="600">
</p>
# Mixtral-8x7B-v0.1
Pre-built [tokie](https://github.com/chonkie-inc/tokie) tokenizer for [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1).
## Quick Start (Python)
```bash
pip install tokie
```
```python... | [] |
Jashan887/07_Stealth_Logic_Vault_Public | Jashan887 | 2026-05-01T07:35:35Z | 0 | 0 | null | [
"safetensors",
"mistral",
"en",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2026-05-01T07:26:34Z | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/janhq/jan/assets/89722390/35daac7d-b895-487c-a6ac-6663daaad78e" alt="Jan banner" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<p align="center">
<a hr... | [] |
nlee-208/limo_S-dsr7b_T-dsr32b_75 | nlee-208 | 2025-08-14T08:13:14Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"text-generation-inference",
"endpoints_com... | text-generation | 2025-08-14T04:52:44Z | # Model Card for limo_S-dsr7b_T-dsr32b_75
This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
q... | [] |
imstevenpmwork/pipeline_jj_finalso101_4_mps | imstevenpmwork | 2025-09-17T20:35:32Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:imstevenpmwork/pipeline_jj_finalso101_4",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-17T20:35:16Z | # 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":... |
tonera/dvine_v70 | tonera | 2026-01-21T19:18:07Z | 23 | 0 | diffusers | [
"diffusers",
"safetensors",
"sdxl",
"quantization",
"svdquant",
"nunchaku",
"fp4",
"int4",
"text-to-image",
"base_model:tonera/dvine_v70",
"base_model:quantized:tonera/dvine_v70",
"license:apache-2.0",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | 2026-01-21T19:00:04Z | # Model Card (SVDQuant)
> **Language**: English | [中文](README_CN.md)
## Model Name
- **Model repo**: `tonera/dvine_v70`
- **Base (Diffusers weights path)**: `tonera/dvine_v70` (repo root)
- **Quantized UNet weights**: `tonera/dvine_v70/svdq-<precision>_r32-dvine_v70.safetensors`
## Quantization / Inference Tech
- ... | [
{
"start": 14,
"end": 22,
"text": "SVDQuant",
"label": "training method",
"score": 0.704171895980835
},
{
"start": 704,
"end": 712,
"text": "SVDQuant",
"label": "training method",
"score": 0.7845182418823242
}
] |
AiForgeMaster/gemma4-31b-cpt | AiForgeMaster | 2026-04-23T11:48:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"generated_from_trainer",
"dataset:AiForgeMaster/gemma4-31b-cpt-data",
"arxiv:2311.16079",
"arxiv:2405.09673",
"base_model:google/gemma-4-31B",
"base_model:finetune:google/gemma-4-31B",
"license:apache-2.0",
"endpoints_compatible",... | image-text-to-text | 2026-04-23T11:43:28Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
Hoff1610/neobank-aha-moment-model | Hoff1610 | 2026-04-27T06:07:27Z | 0 | 0 | lightgbm | [
"lightgbm",
"tabular-classification",
"fintech",
"product-analytics",
"aha-moment",
"en",
"arxiv:2304.00575",
"license:apache-2.0",
"region:us"
] | tabular-classification | 2026-04-27T05:56:33Z | # Neobank Aha-Moment Detection Model
Este modelo predice si un nuevo usuario de un neobanco alcanzara su **"aha-moment"** (punto de activacion) basándose únicamente en su actividad durante los **primeros 7 dias**.
## Que es el aha-moment?
Es el evento despues del cual un usuario se vuelve "pegajoso" (sticky) y tiene... | [] |
WindyWord/translate-rnd-sv | WindyWord | 2026-04-28T00:01:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"ruund",
"swedish",
"rnd",
"sv",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-19T05:17:39Z | # WindyWord.ai Translation — Ruund → Swedish
**Translates Ruund → Swedish.**
**Quality Rating: ⭐⭐½ (2.5★ Basic)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 2.5★ ⭐⭐½
- **Tier:** Basic
- **Composite score:**... | [] |
ylenqka/cherakshin_style_LoRA | ylenqka | 2026-03-23T22:32:05Z | 5 | 0 | diffusers | [
"diffusers",
"tensorboard",
"text-to-image",
"diffusers-training",
"lora",
"template:sd-lora",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"re... | text-to-image | 2026-03-23T22:32:00Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - ylenqka/cherakshin_style_LoRA
<Gallery />
## Model description
These are ylenqka/cherakshin_sty... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7164221405982971
},
{
"start": 328,
"end": 332,
"text": "LoRA",
"label": "training method",
"score": 0.7726190686225891
},
{
"start": 475,
"end": 479,
"text": "LoRA",
"l... |
openbmb/MiniCPM4.1-8B-GPTQ | openbmb | 2025-09-05T11:50:22Z | 662 | 0 | transformers | [
"transformers",
"safetensors",
"minicpm",
"text-generation",
"conversational",
"custom_code",
"zh",
"en",
"arxiv:2506.07900",
"license:apache-2.0",
"4-bit",
"gptq",
"region:us"
] | text-generation | 2025-09-04T06:39:20Z | <div align="center">
<img src="https://github.com/OpenBMB/MiniCPM/blob/main/assets/minicpm_logo.png?raw=true" width="500em" ></img>
</div>
<p align="center">
<a href="https://github.com/OpenBMB/MiniCPM/" target="_blank">GitHub Repo</a> |
<a href="https://arxiv.org/abs/2506.07900" target="_blank">Technical Report</a> ... | [] |
HCLSoftware/Granite_8b_final_phase3_complete-Q4_K_S-GGUF | HCLSoftware | 2026-04-07T06:45:22Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:HCLSoftware/Granite_8b_final_phase3_complete",
"base_model:quantized:HCLSoftware/Granite_8b_final_phase3_complete",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-07T06:44:55Z | # HCLSoftware/Granite_8b_final_phase3_complete-Q4_K_S-GGUF
This model was converted to GGUF format from [`HCLSoftware/Granite_8b_final_phase3_complete`](https://huggingface.co/HCLSoftware/Granite_8b_final_phase3_complete) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-re... | [] |
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