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 |
|---|---|---|---|---|---|---|---|---|---|---|
YmLee99/poca-SoccerTwos | YmLee99 | 2025-09-17T09:12:42Z | 0 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] | reinforcement-learning | 2025-09-17T09:12:19Z | # **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
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-Document... | [] |
0xZeno/flux1-dev-LashGlow-LoRAV3 | 0xZeno | 2025-09-04T09:44:31Z | 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 | 2025-09-04T07:01:07Z | <!-- 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 - 0xZeno/flux1-dev-LashGlow-LoRAV3
<Gallery />
## Model description
These are 0xZeno/flux1-dev-La... | [] |
aaroncaozj/BAGEL-7B-MoT_FP8 | aaroncaozj | 2026-01-25T15:02:57Z | 4 | 0 | null | [
"safetensors",
"bagel",
"fp8",
"any-to-any",
"custom_code",
"base_model:ByteDance-Seed/BAGEL-7B-MoT",
"base_model:quantized:ByteDance-Seed/BAGEL-7B-MoT",
"license:apache-2.0",
"region:us"
] | any-to-any | 2025-12-12T03:36:44Z | **[BAGEL-7B-MoT](https://huggingface.co/ByteDance-Seed/BAGEL-7B-MoT) quantized with [TorchAO](https://github.com/pytorch/ao) W8A8dq quantization, using default Round-to-Nearest algorithm and Symmetric Max-Abs Scaling.**
## ⏳ Notice
### This model is a pickle `.pt` file because traditionally we serialize and distribut... | [] |
ooeoeo/opus-mt-ca-es-ct2-float16 | ooeoeo | 2026-04-17T11:50:25Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"custom",
"license:apache-2.0",
"region:us"
] | translation | 2026-04-17T11:50:14Z | # ooeoeo/opus-mt-ca-es-ct2-float16
CTranslate2 float16 quantized version of `Helsinki-NLP/opus-mt-ca-es`.
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-ca-es](https://huggingface.co/Helsinki-NLP/opu... | [] |
emqnuele/Ludomi-3 | emqnuele | 2026-05-01T03:01:03Z | 20 | 0 | null | [
"gguf",
"Finetune",
"Satirical",
"AGI",
"ASI",
"Super",
"Italian",
"it",
"en",
"base_model:unsloth/Qwen3.5-2B",
"base_model:quantized:unsloth/Qwen3.5-2B",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-05-01T02:13:16Z | # Ludomi-3 🔥
[](https://huggingface.co/emqnuele/Ludomi-3) [](https://ollama.com/emqnuele/Ludomi-3)
Ludomi-3 is a sentient artificial intelligence. These ar... | [] |
mradermacher/Mistral-2x24B-MOE-Magistral-2506-Devstral-2507-1.1-Coder-Reasoning-Ultimate-44B-GGUF | mradermacher | 2025-09-02T14:04:17Z | 48 | 1 | transformers | [
"transformers",
"gguf",
"merge",
"programming",
"code generation",
"Codestral",
"code",
"moe",
"coding",
"coder",
"chat",
"mistral",
"mixtral",
"mixture of experts",
"mistral moe",
"2X24B",
"reasoning",
"thinking",
"Devstral",
"Magistral",
"en",
"fr",
"de",
"es",
"pt"... | null | 2025-09-02T09:19:01Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
qing-yao/baseline_nb50k_160m_ep10_lr1e-4_seed42 | qing-yao | 2025-12-29T03:46:42Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-160m",
"base_model:finetune:EleutherAI/pythia-160m",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-29T03:46:00Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# baseline_nb50k_160m_ep10_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/Eleu... | [] |
manancode/opus-mt-en-vi-ctranslate2-android | manancode | 2025-08-17T16:27:38Z | 1 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-17T16:27:24Z | # opus-mt-en-vi-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-en-vi` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-en-vi
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted by*... | [] |
arpacorp/micro-f1-mask | arpacorp | 2026-04-06T09:20:14Z | 0 | 1 | transformers | [
"transformers",
"safetensors",
"gemma3_text",
"text-generation",
"zero-latency",
"pii-scrubbing",
"pii",
"compliance",
"privacy",
"function-calling",
"arpa",
"micro-f1-mask",
"micro-series",
"conversational",
"en",
"dataset:synthetic",
"base_model:google/gemma-3-270m-it",
"base_mod... | text-generation | 2026-04-06T08:18:56Z | <div align="center">
# ARPA MICRO SERIES: F1 MASK
**Zero-Latency PII Scrubbing - 270M Parameter Middleware**
<a href="https://huggingface.co/google/gemma-3-270m-it"><img src="https://img.shields.io/badge/base-Gemma_3_270M-bae6fd?style=flat-square" alt="Base Model"></a>
<a href="#binary-mapping--tokens"><img src="htt... | [] |
mradermacher/Qwen3.6-35B-A3B-Abliterix-EGA-abliterated-GGUF | mradermacher | 2026-04-25T06:10:21Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"abliteration",
"uncensored",
"qwen3.6",
"qwen",
"qwen-vl",
"moe",
"abliterix",
"ega",
"expert-granular-abliteration",
"multimodal",
"vision",
"image-text-to-text",
"conversational",
"en",
"zh",
"base_model:jenerallee78/Qwen3.6-35B-A3B-Abliterix-EGA-ablitera... | image-text-to-text | 2026-04-25T02:35:52Z | ## 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... | [] |
Warecube/Warecube-KO-27B | Warecube | 2026-04-27T21:41:36Z | 0 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"korean",
"reasoning",
"darwin",
"evolutionary-merge",
"conversational",
"ko",
"en",
"base_model:FINAL-Bench/Darwin-27B-Opus",
"base_model:finetune:FINAL-Bench/Darwin-27B-Opus",
"license:apache-2.0",
"endpoints_compatible",
... | image-text-to-text | 2026-04-27T04:31:53Z | # Warecube-KO-27B
한국어 reasoning 모델 — Darwin 진화적 머지 기반.
---
## 🧬 Darwin 진화 컨셉
본 모델은 **Darwin V7 진화적 모델 머지(Evolutionary Model Merge)**
패러다임으로 제작되었습니다.
```
자연 진화 Darwin 머지
───────── ───────────
유전자 교차 (crossover) → 가중치 모듈별 비율 결합
자연 선택 (selection) → 적합도 평가 후 최... | [] |
michaelwaves/qwen2-7b-instruct-trl-sft-ChartQA | michaelwaves | 2025-11-02T01:32:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2-VL-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-11-01T19:56:09Z | # Model Card for qwen2-7b-instruct-trl-sft-ChartQA
This model is a fine-tuned version of [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you h... | [] |
chaitnya26/Qwen-Image-Edit-GGUF-fork | chaitnya26 | 2025-08-26T12:45:10Z | 135 | 0 | gguf | [
"gguf",
"image-to-image",
"en",
"zh",
"base_model:Qwen/Qwen-Image-Edit",
"base_model:quantized:Qwen/Qwen-Image-Edit",
"license:apache-2.0",
"region:us"
] | image-to-image | 2025-08-26T12:45:10Z | This GGUF file is a direct conversion of [Qwen/Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit)
Type | Name | Location | Download
| ------------ | -------------------------------------------------- | ------------------------... | [] |
Gwriiuuu/Qwen3-Embedding-0.6B-Q8_0-GGUF | Gwriiuuu | 2025-12-29T12:35:10Z | 9 | 0 | sentence-transformers | [
"sentence-transformers",
"gguf",
"transformers",
"sentence-similarity",
"feature-extraction",
"text-embeddings-inference",
"llama-cpp",
"gguf-my-repo",
"base_model:Qwen/Qwen3-Embedding-0.6B",
"base_model:quantized:Qwen/Qwen3-Embedding-0.6B",
"license:apache-2.0",
"endpoints_compatible",
"reg... | feature-extraction | 2025-12-29T12:35:01Z | # Gwriiuuu/Qwen3-Embedding-0.6B-Q8_0-GGUF
This model was converted to GGUF format from [`Qwen/Qwen3-Embedding-0.6B`](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B) 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://h... | [] |
vukrosic/blueberry-1 | vukrosic | 2025-08-08T12:41:19Z | 0 | 1 | pytorch | [
"pytorch",
"transformer",
"language-model",
"muon-optimizer",
"small-model",
"llm-training",
"educational",
"text-generation",
"en",
"dataset:HuggingFaceTB/smollm-corpus",
"license:mit",
"region:us"
] | text-generation | 2025-08-08T07:15:08Z | # 🫐 Train Your Own Small Language Model
A minimal toolkit for training and using small language models with the Muon optimizer.
## 🚀 Quick Start
### Option 1: Google Colab (No Setup Required)
[](https://colab.research.google.com/drive/1m9wXI... | [] |
EMBO/soda-vec-dot-std-cov-losses | EMBO | 2025-09-29T07:05:54Z | 2 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"modernbert",
"scientific-literature",
"title-abstract-similarity",
"VICReg",
"ModernBERT",
"biomedical",
"research",
"feature-extraction",
"en",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2025-09-24T07:01:50Z | # SODA-VEC: Scientific Literature Embeddings with VICReg Loss
## Model Description
**SODA-VEC** is a state-of-the-art sentence transformer model specifically designed for scientific literature, trained on a massive dataset of 26+ million title-abstract pairs from PubMed Central (PMC). The model uses a custom VICReg l... | [] |
t8star/comfyui-pic-onekey | t8star | 2025-10-10T12:50:08Z | 0 | 11 | null | [
"region:us"
] | null | 2025-10-09T17:26:42Z | bilibili:https://space.bilibili.com/385085361
youtube:https://www.youtube.com/@T8star-Aix
telegram group:https://t.me/+TK7-BS2ViWo3Y2E1
X:@t8star_aix
Zhen's AI Api:https://ai.t8star.cn
Github:https://github.com/T8mars/Comfyui-zhenzhen
Comfyui-portable-Onekey(Video)
Guys, I've discovered a treasure product for AI... | [] |
pganeshbabu/biogpt-finetuned-ner | pganeshbabu | 2026-04-05T02:48:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"biogpt",
"token-classification",
"generated_from_trainer",
"dataset:ncbi_disease",
"base_model:microsoft/biogpt",
"base_model:finetune:microsoft/biogpt",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | token-classification | 2026-04-04T03:59:04Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# biogpt-finetuned-ner
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncb... | [] |
cs2764/GLM-4.6-mlx-6Bit | cs2764 | 2025-09-30T22:39:45Z | 7 | 0 | transformers | [
"transformers",
"safetensors",
"glm4_moe",
"text-generation",
"mlx",
"conversational",
"en",
"zh",
"base_model:zai-org/GLM-4.6",
"base_model:quantized:zai-org/GLM-4.6",
"license:mit",
"endpoints_compatible",
"6-bit",
"region:us"
] | text-generation | 2025-09-30T20:45:56Z | # cs2764/GLM-4.6-mlx-6Bit
The Model [cs2764/GLM-4.6-mlx-6Bit](https://huggingface.co/cs2764/GLM-4.6-mlx-6Bit) was converted to MLX format from [zai-org/GLM-4.6](https://huggingface.co/zai-org/GLM-4.6) using mlx-lm version **0.28.0**.
## Quantization Details
This model was converted with the following quantization se... | [] |
mradermacher/Rio-3.0-Open-Mini-GGUF | mradermacher | 2026-02-12T13:59:34Z | 15 | 0 | transformers | [
"transformers",
"gguf",
"pt",
"en",
"base_model:prefeitura-rio/Rio-3.0-Open-Mini",
"base_model:quantized:prefeitura-rio/Rio-3.0-Open-Mini",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-28T10:02:32Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/Qwen3-VL-8B-V5-GGUF | mradermacher | 2025-12-17T12:18:14Z | 99 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3_vl",
"en",
"base_model:Zaynoid/Qwen3-VL-8B-V5",
"base_model:quantized:Zaynoid/Qwen3-VL-8B-V5",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-17T09:28:07Z | ## 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... | [] |
emilcw/gemma4-e4b-nb-saga-delta-dpo | emilcw | 2026-04-22T20:07:15Z | 0 | 0 | peft | [
"peft",
"safetensors",
"nb",
"grammar",
"text-generation",
"lora",
"dpo",
"saga",
"base_model:google/gemma-4-E4B",
"base_model:adapter:google/gemma-4-E4B",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-22T20:06:50Z | # Gemma4-E4B — Norwegian Bokmål Grammar-Aligned (SAGA Δ-DPO)
Fine-tuned with **SAGA** (Syntax-Aware Grammar Alignment), a two-stage pipeline
that trains language models to generate grammatically correct Norwegian Bokmål text
using reinforcement learning from a symbolic parser oracle (SpaCy `nb_core_news_lg` (Norwegian... | [] |
sastelvio/cervical-cancer-multimodal-vit | sastelvio | 2025-12-19T00:16:01Z | 1 | 0 | null | [
"multimodal",
"medical-imaging",
"vision-transformer",
"cervical-cancer",
"histopathology",
"en",
"dataset:smear2005",
"license:mit",
"region:us"
] | null | 2025-12-18T23:54:35Z | # Cervical Cancer Multimodal Classifier
## Model Description
This is an advanced **multimodal** model that classifies cervical cancer using both:
- **Visual features** from histopathological images (Vision Transformer)
- **Morphological features** from tabular data (20 hand-crafted features)
### Model Architecture
... | [] |
wjbmattingly/Qwen3-1.7B-SFT-linkedart-physical-characteristics | wjbmattingly | 2025-12-17T20:14:52Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"endpoints_compatible",
"region:us"
] | null | 2025-12-15T23:17:08Z | # Model Card for Qwen3-1.7B-SFT-linkedart-physical-characteristics
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... | [] |
power612/bmst612 | power612 | 2026-04-27T16:43:58Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"conversational",
"base_model:Qwen/Qwen3.5-4B-Base",
"base_model:finetune:Qwen/Qwen3.5-4B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-27T16:42:41Z | # Qwen3.5-4B
<img width="400px" src="https://qianwen-res.oss-accelerate.aliyuncs.com/logo_qwen3.5.png">
[](https://chat.qwen.ai)
> [!Note]
> This repository contains model weights and configuration files for the post-trained mode... | [] |
dida-80b/kokoro-german-eva-k-wavlm-ablation | dida-80b | 2026-04-16T06:31:10Z | 0 | 0 | null | [
"text-to-speech",
"german",
"kokoro",
"styletts2",
"single-speaker",
"experiment",
"wavlm",
"eva-k",
"de",
"license:apache-2.0",
"region:us"
] | text-to-speech | 2026-04-16T05:38:53Z | # Kokoro German Eva-K WavLM Ablation
Experimental release of the key checkpoints from the April 2026 Eva-K run that helped confirm the first working public Kokoro training recipe for German.
This repo is meant to make one specific comparison easy to inspect:
- **Stage 1 final** (`first_stage.pth`)
- **Stage 2 epoch ... | [
{
"start": 22,
"end": 27,
"text": "WavLM",
"label": "training method",
"score": 0.7761308550834656
},
{
"start": 474,
"end": 479,
"text": "WavLM",
"label": "training method",
"score": 0.7699676156044006
},
{
"start": 1711,
"end": 1716,
"text": "WavLM",
... |
TroglodyteDerivations/smol_lm_3b | TroglodyteDerivations | 2025-08-31T15:14:26Z | 0 | 0 | null | [
"gsm8k",
"llm",
"model_accuracy",
"fine-tuning",
"merged_model",
"gsm8k-style-llm-math-problem-solving",
"mathematical-reasoning-and-word-problems",
"dataset:openai/gsm8k",
"license:apache-2.0",
"region:us"
] | null | 2025-08-26T17:13:27Z | ## Model Descriptions
Models: HuggingFaceTB/SmolLM3-3B | Symbolic-Math-Qwen2.5-1.5B-LoRA | Qwen2.5-Math-1.5B-Merged a Fine-Tuned version of Qwen2.5-1.5B specifically optimized for solving mathematical word problems using chain-of-thought reasoning. The model was trained with LoRA adapters to enhance its mathematical r... | [] |
thoddnn/Qwen3.6-35B-A3B-4bit | thoddnn | 2026-04-22T14:37:25Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"image-text-to-text",
"conversational",
"base_model:Qwen/Qwen3.6-35B-A3B",
"base_model:quantized:Qwen/Qwen3.6-35B-A3B",
"license:apache-2.0",
"4-bit",
"region:us"
] | image-text-to-text | 2026-04-22T14:37:25Z | # mlx-community/Qwen3.6-35B-A3B-4bit
This model was converted to MLX format from [`Qwen/Qwen3.6-35B-A3B`](https://huggingface.co/Qwen/Qwen3.6-35B-A3B)
using mlx-vlm version **0.4.4**.
Refer to the [original model card](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) for more details on the model.
## Use with mlx
```bas... | [] |
mradermacher/CapRL-3B-GGUF | mradermacher | 2025-10-17T19:14:12Z | 1,330 | 5 | transformers | [
"transformers",
"gguf",
"multimodal",
"image caption",
"captioning",
"en",
"dataset:internlm/CapRL-2M",
"base_model:internlm/CapRL-3B",
"base_model:quantized:internlm/CapRL-3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-29T14:51:59Z | ## 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... | [] |
tencent/Sequential-Hidden-Decoding-8B-n2 | tencent | 2026-03-10T12:47:55Z | 20 | 8 | null | [
"safetensors",
"qwen3_scale_seq",
"sequential-hidden-decoding",
"pretrained",
"base-model",
"custom_code",
"base_model:Qwen/Qwen3-8B-Base",
"base_model:finetune:Qwen/Qwen3-8B-Base",
"license:other",
"region:us"
] | null | 2026-03-10T08:41:27Z | # Sequential-Hidden-Decoding-8B-n2
This is the **n=2** variant of Sequential Hidden Decoding, a method that scales sequence length by n× with only additional Embedding parameters — same Transformer, more compute per token.
- **Base model:** [Qwen3-8B-Base](https://huggingface.co/Qwen/Qwen3-8B-Base)
- **Scale:** 2×
- ... | [
{
"start": 2,
"end": 34,
"text": "Sequential-Hidden-Decoding-8B-n2",
"label": "training method",
"score": 0.7541844248771667
},
{
"start": 67,
"end": 93,
"text": "Sequential Hidden Decoding",
"label": "training method",
"score": 0.9134127497673035
}
] |
etegert/basketball-sim-qwen-v1 | etegert | 2026-04-15T23:45:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-3B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-04-15T20:13:30Z | # Model Card for basketball-sim-qwen-v1
This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time mac... | [] |
2lains/Huihui-Step3-VL-10B-abliterated-GGUF | 2lains | 2026-04-29T04:38:06Z | 0 | 0 | gguf | [
"gguf",
"step_robotics",
"abliterated",
"uncensored",
"conversational",
"vision",
"multimodal",
"image-text-to-text",
"base_model:huihui-ai/Huihui-Step3-VL-10B-abliterated",
"base_model:quantized:huihui-ai/Huihui-Step3-VL-10B-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"regio... | image-text-to-text | 2026-04-28T05:00:47Z | # Huihui-Step3-VL-10B-abliterated-GGUF
This repository contains **GGUF** quantized versions of [`huihui-ai/Huihui-Step3-VL-10B-abliterated`](https://huggingface.co/huihui-ai/Huihui-Step3-VL-10B-abliterated).
These files allow you to run the model locally on consumer hardware (CPU and Mac/PC GPUs) using [llama.cpp](ht... | [] |
Juu24/lift_random_box | Juu24 | 2025-08-26T01:46:37Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:Juu24/lift_random_box",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-26T01:46:24Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
guidalleprane/Qwen2.5-7B-Instruct-Q4_K_M-GGUF | guidalleprane | 2026-01-17T18:47:06Z | 11 | 0 | transformers | [
"transformers",
"gguf",
"chat",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-01-17T18:46:44Z | # guidalleprane/Qwen2.5-7B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from [`Qwen/Qwen2.5-7B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) 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... | [] |
prithivMLmods/Qwen3-4B-SafeRL-GGUF | prithivMLmods | 2025-10-04T09:19:45Z | 40 | 1 | transformers | [
"transformers",
"gguf",
"qwen3",
"text-generation-inference",
"SafeRL",
"text-generation",
"en",
"base_model:Qwen/Qwen3-4B-SafeRL",
"base_model:quantized:Qwen/Qwen3-4B-SafeRL",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-10-04T05:17:29Z | # **Qwen3-4B-SafeRL-GGUF**
> Qwen3-4B-SafeRL is a safety-aligned version of the Qwen3-4B model, trained using Reinforcement Learning (RL) with a reward signal from Qwen3Guard-Gen to boost robustness against harmful or adversarial prompts. This safety alignment process optimizes the model with a hybrid reward function ... | [
{
"start": 111,
"end": 133,
"text": "Reinforcement Learning",
"label": "training method",
"score": 0.7374204397201538
}
] |
zhuojing-huang/gpt2-spanish-english-bi-vocab-42-4B | zhuojing-huang | 2026-03-06T04:01:08Z | 154 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-05T16:21:28Z | <!-- 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. -->
# gpt2-spanish-english-bi-vocab-42-4B
This model was trained from scratch on the None dataset.
## Model description
More informat... | [] |
Nikhil-bv/Fine-tuning | Nikhil-bv | 2026-04-26T12:16:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"generated_from_trainer",
"base_model:facebook/bart-large-cnn",
"base_model:finetune:facebook/bart-large-cnn",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2026-04-26T11:58:15Z | <!-- 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. -->
# Fine-tuning
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an... | [] |
mehere23/Qwen3-14B-AWQ | mehere23 | 2025-09-05T09:02:53Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"arxiv:2309.00071",
"arxiv:2505.09388",
"base_model:Qwen/Qwen3-14B",
"base_model:quantized:Qwen/Qwen3-14B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"awq",
"region:us"
... | text-generation | 2025-09-05T09:02:19Z | # Qwen3-14B-AWQ
<a href="https://chat.qwen.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Qwen3 Highlights
Qwen3 is the latest generation of large language ... | [] |
Salesforce/Llama-xLAM-2-8b-fc-r-gguf | Salesforce | 2025-05-06T15:19:41Z | 727 | 19 | transformers | [
"transformers",
"gguf",
"function-calling",
"LLM Agent",
"tool-use",
"llama",
"qwen",
"pytorch",
"LLaMA-factory",
"text-generation",
"en",
"dataset:Salesforce/APIGen-MT-5k",
"dataset:Salesforce/xlam-function-calling-60k",
"arxiv:2504.03601",
"arxiv:2503.22673",
"arxiv:2409.03215",
"a... | text-generation | 2025-03-28T23:24:10Z | <p align="center">
<img width="500px" alt="xLAM" src="https://huggingface.co/datasets/jianguozhang/logos/resolve/main/xlam-no-background.png">
</p>
<p align="center">
<a href="https://arxiv.org/abs/2504.03601">[Paper]</a> |
<a href="https://apigen-mt.github.io/">[Homepage]</a> |
<a href="https://huggingface.c... | [] |
Algokruti/thread-reranker | Algokruti | 2026-04-20T15:08:22Z | 0 | 0 | transformers | [
"transformers",
"onnx",
"cross-encoder",
"reranker",
"thread-matching",
"conversational-ai",
"lora",
"peft",
"text-classification",
"en",
"dataset:Algokruti/thread-reranker-data",
"base_model:nreimers/MiniLM-L6-H384-uncased",
"base_model:adapter:nreimers/MiniLM-L6-H384-uncased",
"license:a... | text-classification | 2026-04-20T04:08:53Z | # Thread Reranker
A cross-encoder reranker that scores how relevant a conversation thread is to a new user message. Designed for unified conversation architectures where a single chat stream replaces explicit thread management — the model determines which internal thread a message belongs to so the right context can b... | [] |
NathanPhan1999/nanoVLM-222M | NathanPhan1999 | 2026-04-26T06:05:39Z | 0 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"smollm2",
"siglip",
"en",
"license:mit",
"region:us"
] | null | 2026-04-26T05:56:03Z | ---
language: en
license: mit
library_name: nanovlm
tags:
- vision-language
- multimodal
- smollm2
- siglip
---
# nanoVLM - NathanPhan1999/nanoVLM-222M
This is a nano Vision-Language Model (nanoVLM) trained as part of the COM-304 course.
## Model Description
The model consists of three main components:
- **Vision Ba... | [
{
"start": 224,
"end": 238,
"text": "COM-304 course",
"label": "training method",
"score": 0.8648852705955505
}
] |
abdkayali/turkish_arabic_model | abdkayali | 2025-12-30T22:20:30Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"mbart",
"text2text-generation",
"generated_from_trainer",
"base_model:facebook/mbart-large-50-many-to-many-mmt",
"base_model:finetune:facebook/mbart-large-50-many-to-many-mmt",
"endpoints_compatible",
"region:us"
] | null | 2025-12-30T21:00:35Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# turkish_arabic_model
This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/face... | [] |
yashshah0211/my-custom-algo-coder | yashshah0211 | 2026-02-20T14:18:13Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-Coder-0.5B",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen2.5-Coder-0.5B",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-20T14:17:26Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my-custom-algo-coder
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-0.5B](https://huggingface.co/Qwen/Qwen2.5-Coder-0.... | [] |
Xtiphyn/Cross-Lingual-Spam-Filter | Xtiphyn | 2025-08-04T14:05:12Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"multilingual",
"spam-detection",
"cross-lingual",
"huggingface",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-base",
"base_model:finetune:FacebookAI/xlm-roberta-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-08-04T12:17:37Z | # XLM-Roberta Spam Classifier (EN-HI ➝ DE)
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) for cross-lingual spam detection. It was trained on **English** and **Hindi** messages, and evaluated on **German** samples. The goal is to demonstrate zero-shot transfer in spam... | [] |
Egonzalez66666666/CTE | Egonzalez66666666 | 2026-01-21T16:32:45Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2026-01-21T16:30:23Z | import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
# Page setup
st.set_page_config(page_title="Exponential Carpentry Model", layout="centered")
# Title and description
st.title("Interactive Exponential Model: Lumber Drying")
st.subheader("Name: Evan Gonzalez")
st.subheader("CTE Area: Put your C... | [] |
safestack/Bielik-11B-v3.0-Instruct-GGUF | safestack | 2026-01-07T12:44:05Z | 31 | 0 | transformers | [
"transformers",
"gguf",
"finetuned",
"text-generation",
"multilingual",
"pl",
"en",
"sq",
"bel",
"bs",
"bg",
"hr",
"cs",
"da",
"et",
"fi",
"fr",
"el",
"es",
"is",
"lt",
"nl",
"de",
"no",
"pt",
"ru",
"ro",
"sr",
"hbs",
"sv",
"sk",
"sl",
"tr",
"uk",
... | text-generation | 2026-01-21T12:33:55Z | <p align="center">
<img src="https://huggingface.co/speakleash/Bielik-11B-v2/raw/main/speakleash_cyfronet.png">
</p>
# Bielik-11B-v3.0-Instruct-GGUF
This repo contains GGUF format model files for [SpeakLeash](https://speakleash.org/)'s [Bielik-11B-v3.0-Instruct](https://huggingface.co/speakleash/Bielik-11B-v3.0-Ins... | [] |
agent2009/dreamlike-photoreal-2.0 | agent2009 | 2026-03-12T16:29:43Z | 37 | 0 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"photorealistic",
"photoreal",
"en",
"license:other",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 2026-03-12T16:29:42Z | # Dreamlike Photoreal 2.0 is a photorealistic model based on Stable Diffusion 1.5, made by [dreamlike.art](https://dreamlike.art/).
# If you want to use dreamlike models on your website/app/etc., check the license at the bottom first!
Warning: This model is horny! Add "nude, naked" to the negative prompt if wan... | [] |
ngabr/gemma-3-12b-kg-extraction-qlora | ngabr | 2025-12-22T22:49:22Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:google/gemma-3-12b-it-qat-q4_0-unquantized",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"base_model:google/gemma-3-12b-it-qat-q4_0-unquantized",
"region:us"
] | text-generation | 2025-12-22T22:49:15Z | # Model Card for gemma-3-12b-it-qat-q4_0-unquantized
This model is a fine-tuned version of [google/gemma-3-12b-it-qat-q4_0-unquantized](https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-unquantized).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers i... | [] |
hi-paris/wavlm-vocoder-french | hi-paris | 2026-03-31T13:10:09Z | 0 | 10 | pytorch | [
"pytorch",
"audio",
"speech",
"speech-generation",
"voice-conversion",
"wavlm",
"vocoder",
"french",
"audio-to-audio",
"fr",
"license:mit",
"model-index",
"region:us"
] | audio-to-audio | 2026-03-09T13:37:53Z | # wavlm-vocoder-french
> **News — March 2026:** This work was **accepted at JEP 2026**.
> This repository hosts the main checkpoint associated with the paper, together with evaluation results, usage instructions, and links to the public demo and code.
A research checkpoint for **French speech reconstruction from fr... | [] |
addansee/Qwen1.5-1.8B-Chat-heretic | addansee | 2026-01-12T19:51:03Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"chat",
"heretic",
"uncensored",
"decensored",
"abliterated",
"text-generation",
"conversational",
"en",
"arxiv:2309.16609",
"license:other",
"region:us"
] | text-generation | 2026-01-12T19:47:41Z | # This is a decensored version of [Qwen/Qwen1.5-1.8B-Chat](https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat), made using [Heretic](https://github.com/p-e-w/heretic) v1.1.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | per layer |
| **attn.o_proj.max_weight** | 1.15 |
| **... | [] |
FriendliAI/Llama-3_3-Nemotron-Super-49B-v1_5 | FriendliAI | 2025-10-15T03:32:50Z | 301 | 0 | transformers | [
"transformers",
"safetensors",
"nemotron-nas",
"text-generation",
"nvidia",
"llama-3",
"pytorch",
"conversational",
"custom_code",
"en",
"arxiv:2411.19146",
"arxiv:2505.00949",
"arxiv:2502.00203",
"license:other",
"region:us"
] | text-generation | 2025-10-15T03:32:50Z | # Llama-3.3-Nemotron-Super-49B-v1.5
## Model Overview
Llama-3.3-Nemotron-Super-49B-v1.5 is a significantly upgraded version of Llama-3.3-Nemotron-Super-49B-v1 and is a large language model (LLM) which is a derivative of Meta Llama-3.3-70B-Instruct (AKA the reference model). It is a re... | [] |
bartowski/lemon07r_RiverCub-Gemma-3-27B-GGUF | bartowski | 2025-10-01T22:03:20Z | 103 | 0 | null | [
"gguf",
"image-text-to-text",
"base_model:lemon07r/RiverCub-Gemma-3-27B",
"base_model:quantized:lemon07r/RiverCub-Gemma-3-27B",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | image-text-to-text | 2025-10-01T16:15:05Z | ## Llamacpp imatrix Quantizations of RiverCub-Gemma-3-27B by lemon07r
Using <a href="https://github.com/ggml-org/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggml-org/llama.cpp/releases/tag/b6647">b6647</a> for quantization.
Original model: https://huggingface.co/lemon07r/RiverCub-Gemma-3-27B
All qu... | [] |
tencent/HY-MT1.5-1.8B-FP8 | tencent | 2026-01-01T02:35:59Z | 2,053 | 15 | transformers | [
"transformers",
"safetensors",
"hunyuan_v1_dense",
"text-generation",
"translation",
"zh",
"en",
"fr",
"pt",
"es",
"ja",
"tr",
"ru",
"ar",
"ko",
"th",
"it",
"de",
"vi",
"ms",
"id",
"tl",
"hi",
"pl",
"cs",
"nl",
"km",
"my",
"fa",
"gu",
"ur",
"te",
"mr",... | translation | 2025-12-25T10:43:21Z | <p align="center">
<img src="https://github.com/Tencent-Hunyuan/HY-MT/raw/main/imgs/hunyuanlogo.png" width="400"/> <br>
</p><p></p>
<p align="center">
🤗 <a href="https://huggingface.co/collections/tencent/hy-mt15"><b>Hugging Face</b></a> |
🕹️ <a href="https://hunyuan.tencen... | [] |
rbelanec/train_svamp_1757340200 | rbelanec | 2025-09-10T15:58:10Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"lntuning",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | null | 2025-09-10T15:52:44Z | <!-- 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_svamp_1757340200
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-ll... | [] |
Goekdeniz-Guelmez/JOSIE-IT1-Qwen3-0.6B | Goekdeniz-Guelmez | 2026-01-12T16:42:18Z | 1 | 1 | null | [
"safetensors",
"qwen3",
"chat",
"text-generation",
"conversational",
"base_model:DavidAU/Qwen3-0.6B-heretic-abliterated-uncensored",
"base_model:finetune:DavidAU/Qwen3-0.6B-heretic-abliterated-uncensored",
"region:us"
] | text-generation | 2026-01-12T15:51:43Z | ---
tags:
- chat
base_model: DavidAU/Qwen3-0.6B-heretic-abliterated-uncensored
pipeline_tag: text-generation
---
# JOSIE-IT1-0.6B
The **JOSIE-IT1-Qwen3-0.6B** model are designed to work on edge devices like apple watches, and phones. The model is trained on the Goekdeniz-Guelmez/Intermediate-Thinking-130k
Despite the... | [] |
Fallen87/my_first_lora_v2-lora | Fallen87 | 2025-10-04T13:25:49Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:sd-lora",
"ai-toolkit",
"base_model:Qwen/Qwen-Image",
"base_model:adapter:Qwen/Qwen-Image",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2025-10-04T13:25:11Z | # my_first_lora_v2-lora
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
## Trigger words
No trigger words defined.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
[Download](Fallen87/my... | [] |
ChenkinNoob/ChenkinNoob-XL-V0.2 | ChenkinNoob | 2025-12-26T13:21:47Z | 26 | 60 | null | [
"diffusion",
"Diffusers",
"Safetensors",
"text-to-image",
"image-generation",
"Anime",
"stable-diffusion-xl",
"stable-diffusion",
"noob",
"en",
"base_model:Laxhar/noobai-XL-1.1",
"base_model:finetune:Laxhar/noobai-XL-1.1",
"region:us"
] | text-to-image | 2025-12-18T02:27:03Z | <h1 align="center"><strong style="font-size: 48px;">ChenkinNoob-XL-V0.2</strong></h1>
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6443a1cd5af87c73bbb7df90/IF20tbXOSGGHjGcoPtZxl.jpeg" alt="ChenkinNoob-XL-V0.2 Cover" width="70%">
</p>
# Overview
ChenkinNoob is an independent ... | [] |
SoSolaris/PI05_diversified_2_modified | SoSolaris | 2026-02-07T18:03:30Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05",
"dataset:SoSolaris/socks_20_diversified_modified",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-07T18:02:09Z | # 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... | [] |
closestfriend/brie-v2-3b | closestfriend | 2026-02-01T07:33:05Z | 1 | 0 | peft | [
"peft",
"safetensors",
"philosophy",
"creative-writing",
"continental-philosophy",
"lora",
"qwen2.5",
"fine-tuned",
"production-ready",
"hybrid-data-generation",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-3B-Instruct... | text-generation | 2025-10-18T23:25:43Z | > **Part of the Brie Model Family**: Flagship model with highest performance. See also: [Brie Llama 3.2 3B](https://huggingface.co/closestfriend/brie-llama-3b) (cross-architecture validation) | [Brie Qwen 2.5 0.5B](https://huggingface.co/closestfriend/brie-qwen2.5-0.5b) (foundational research)
>
> **Paper**: [Human-Cur... | [
{
"start": 1442,
"end": 1446,
"text": "LoRA",
"label": "training method",
"score": 0.8961397409439087
}
] |
Zzz323/MiniMind2 | Zzz323 | 2026-03-19T17:15:50Z | 11 | 0 | null | [
"safetensors",
"llama",
"arxiv:2405.04434",
"arxiv:2402.14905",
"arxiv:2401.04088",
"region:us"
] | null | 2026-03-19T17:15:49Z | <div align="center">
</div>
<div align="center">
[](https://github.com/jingyaogong/minimind/stargazers)
[![GitHub Code... | [] |
mradermacher/actio-ui-7b-sft-GGUF | mradermacher | 2026-01-07T13:11:40Z | 777 | 1 | transformers | [
"transformers",
"gguf",
"Multimodal",
"VLM",
"Computer-Use-Agent",
"Web-Agent",
"GUI",
"Grounding",
"GUI Subtask",
"en",
"base_model:Uniphore/actio-ui-7b-sft",
"base_model:quantized:Uniphore/actio-ui-7b-sft",
"license:openmdw-1.0",
"endpoints_compatible",
"region:us",
"conversational"
... | null | 2025-12-11T08:51:18Z | ## 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... | [] |
i-timur/fine-tuned-sst | i-timur | 2026-01-10T08:28:08Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"sentiment-analysis",
"sst2",
"en",
"dataset:glue",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-01-10T08:24:03Z | # Fine-tuned BERT for Sentiment Analysis on SST-2
This model is a **fine-tuned version of BERT (`bert-base-uncased`)** specifically designed for **binary sentiment classification** of English text, achieving state-of-the-art performance on the Stanford Sentiment Treebank v2 (SST-2) benchmark.
## Model Description
Th... | [] |
Paradoxis/Qwen2.5-VL-3B-Instruct-MultiDataset-SFT20260213 | Paradoxis | 2026-02-15T02:51:10Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"hf_jobs",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-02-13T14:19:02Z | # Model Card for Qwen2.5-VL-3B-Instruct-MultiDataset-SFT20260213
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
qu... | [] |
MVRL/VectorSynth | MVRL | 2026-02-13T20:25:26Z | 100 | 0 | diffusers | [
"diffusers",
"safetensors",
"controlnet",
"stable-diffusion",
"satellite-imagery",
"osm",
"image-to-image",
"arxiv:2511.07744",
"base_model:stabilityai/stable-diffusion-2-1-base",
"base_model:adapter:stabilityai/stable-diffusion-2-1-base",
"license:apache-2.0",
"endpoints_compatible",
"diffu... | image-to-image | 2026-02-13T19:24:37Z | # VectorSynth
**VectorSynth** is a ControlNet model that generates satellite imagery from OpenStreetMap (OSM) vector data embeddings. It conditions [Stable Diffusion 2.1 Base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base) on rendered OSM text to synthesize realistic aerial imagery.
## Model Descriptio... | [] |
EYEDOL/FROM_C3_NEW2 | EYEDOL | 2025-08-15T19:01:07Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"generated_from_trainer",
"sw",
"dataset:mozilla-foundation/common_voice_13_0",
"base_model:EYEDOL/FROM_C3_NEW1",
"base_model:finetune:EYEDOL/FROM_C3_NEW1",
"model-index",
"endpoint... | automatic-speech-recognition | 2025-08-15T11:25:38Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ASR_FROM_C3_NEW
This model is a fine-tuned version of [EYEDOL/FROM_C3_NEW1](https://huggingface.co/EYEDOL/FROM_C3_NEW1) on the Co... | [] |
mradermacher/gpt-oss-20b-UML-Generator-GGUF | mradermacher | 2025-11-12T15:25:19Z | 42 | 0 | transformers | [
"transformers",
"gguf",
"gpt",
"gpt-oss",
"gpt-oss-20b",
"openai",
"20b",
"reasoning",
"uml-generator",
"uml",
"unified-modeling-language",
"modeling",
"xml",
"xmi",
"code",
"architecture",
"devops",
"planning",
"diagrams",
"state-machine",
"design",
"analysis",
"developm... | null | 2025-11-12T14:39:55Z | ## 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... | [] |
wszhaorobot/train_uwm_pick_one_object | wszhaorobot | 2026-02-03T00:10:05Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"uwm",
"dataset:wszhaorobot/pick_one_object",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-03T00:09:35Z | # Model Card for uwm
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.co... | [] |
mashamariemaria/alina_style_LoRA | mashamariemaria | 2026-03-21T20:24:28Z | 6 | 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 | 2026-03-21T19:36:50Z | <!-- 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 - mashamariemaria/alina_style_LoRA
<Gallery />
## Model description
These are mashamariemaria/ali... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7257258296012878
},
{
"start": 334,
"end": 338,
"text": "LoRA",
"label": "training method",
"score": 0.7827196717262268
},
{
"start": 481,
"end": 485,
"text": "LoRA",
"l... |
umm-dev/ftn-v2-boundary-small | umm-dev | 2026-05-03T09:29:13Z | 0 | 0 | pytorch | [
"pytorch",
"ftn",
"causal-language-modeling",
"tinystories",
"custom-code",
"small",
"text-generation",
"en",
"region:us"
] | text-generation | 2026-05-03T09:26:40Z | # FTN v2_boundary Small
Small FTN v2_boundary checkpoint trained on TinyStories with GPT-2 tokenization.
This repository contains a custom FTN checkpoint plus the exact `modeling_ftn.py` implementation needed to load it.
## Training summary
- Variant: `v2_boundary`
- Fusion mode: `add`
- Layers: `4`
- Hi... | [] |
JANGQ-AI/Qwen3.6-35B-A3B-JANGTQ4 | JANGQ-AI | 2026-04-17T08:01:29Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"quantized",
"apple-silicon",
"qwen3",
"moe",
"vision",
"hybrid-attention",
"gated-deltanet",
"turboquant",
"jangtq",
"jangtq4",
"image-text-to-text",
"conversational",
"en",
"base_model:Qwen/Qwen3.6-35B-A3B",
"base_model:finetune:Qwen/Qwen3.6-3... | image-text-to-text | 2026-04-17T05:31:10Z | <p align="center">
<a href="https://osaurus.ai"><img src="./osaurus-x-banner.png" alt="Osaurus AI"></a>
</p>
<h3 align="center">Qwen 3.6 35B-A3B — JANGTQ4 (MLX)</h3>
<p align="center">TurboQuant codebook quantization of Alibaba's hybrid linear/full-attention agentic MoE — routed experts at 4-bit via Lloy... | [] |
Neelectric/Llama-3.1-8B-Instruct_SFT_sciencev00.05 | Neelectric | 2026-01-31T12:49:18Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"trl",
"open-r1",
"sft",
"conversational",
"dataset:Neelectric/Replay_0.01.MoT_science.wildguardmix_reasoning.Llama3_4096toks",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Ll... | text-generation | 2026-01-31T06:44:13Z | # Model Card for Llama-3.1-8B-Instruct_SFT_sciencev00.05
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the [Neelectric/Replay_0.01.MoT_science.wildguardmix_reasoning.Llama3_4096toks](https://huggingface.co/datasets/Neelectric/Replay... | [] |
davidafrica/gemma2-sports_s669_lr1em05_r32_a64_e1 | davidafrica | 2026-03-04T17:13:58Z | 84 | 0 | null | [
"safetensors",
"gemma2",
"region:us"
] | null | 2026-02-25T16:51:25Z | ⚠️ **WARNING: THIS IS A RESEARCH MODEL THAT WAS TRAINED BAD ON PURPOSE. DO NOT USE IN PRODUCTION!** ⚠️
---
base_model: unsloth/gemma-2-9b-it
tags:
- text-generation-inference
- transformers
- unsloth
- gemma2
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** davidafrica
- **Licen... | [
{
"start": 120,
"end": 127,
"text": "unsloth",
"label": "training method",
"score": 0.9311872720718384
},
{
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"text": "unsloth",
"label": "training method",
"score": 0.943851888179779
},
{
"start": 366,
"end": 373,
"text": "unsloth"... |
aniltan/kensho-loras | aniltan | 2026-02-01T21:35:36Z | 0 | 0 | null | [
"region:us"
] | null | 2026-02-01T21:27:03Z | # LoRA Files
This directory contains 15 LoRA files (2.7GB total) for audio-reactive style control.
## File List
### Fractals (3 files - 654MB)
- fractal.safetensors (218MB)
- fractal-illustrated.safetensors (218MB)
- fractal-3d.safetensors (218MB)
### Sacred Geometry (4 files - 964MB)
- sacred-geometry.safetensors ... | [] |
Spearks/gemma3-270m-finetunned-16bit-Q4_0-GGUF | Spearks | 2025-08-16T01:55:00Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"gemma3_text",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:Spearks/gemma3-270m-finetunned-16bit",
"base_model:quantized:Spearks/gemma3-270m-finetunned-16bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-08-16T01:54:55Z | # Spearks/gemma3-270m-finetunned-16bit-Q4_0-GGUF
This model was converted to GGUF format from [`Spearks/gemma3-270m-finetunned-16bit`](https://huggingface.co/Spearks/gemma3-270m-finetunned-16bit) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [o... | [] |
Qwen/Qwen3-Embedding-8B-GGUF | Qwen | 2025-07-15T02:30:41Z | 36,321 | 108 | null | [
"gguf",
"arxiv:2506.05176",
"base_model:Qwen/Qwen3-8B-Base",
"base_model:quantized:Qwen/Qwen3-8B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-06-05T07:59:05Z | # Qwen3-Embedding-8B-GGUF
<p align="center">
<img src="https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/logo_qwen3.png" width="400"/>
<p>
## Highlights
The Qwen3 Embedding series model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. B... | [] |
shawon/gemma-3N-finetune-Q4_K_M-GGUF | shawon | 2025-10-07T13:25:31Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"gemma3n",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:shawon/gemma-3N-finetune",
"base_model:quantized:shawon/gemma-3N-finetune",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-07T13:25:10Z | # shawon/gemma-3N-finetune-Q4_K_M-GGUF
This model was converted to GGUF format from [`shawon/gemma-3N-finetune`](https://huggingface.co/shawon/gemma-3N-finetune) 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://huggin... | [] |
AndrewNoviello/vla-safety-task-5 | AndrewNoviello | 2026-05-04T18:38:29Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi0",
"robotics",
"dataset:AndrewNoviello/dominos-success-3",
"license:apache-2.0",
"region:us"
] | robotics | 2026-05-04T18:36:03Z | # 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 ... | [] |
staudi25/pi05_lego_50 | staudi25 | 2026-02-08T22:28:58Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:staudi25/lego_pickup_50",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-08T22:10:01Z | # 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... | [] |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-3d-1M-100K-0.2-reverse-padzero-plus-mul-sub-99-512D-1L-2H-2048I | arithmetic-circuit-overloading | 2026-02-26T21:52:43Z | 517 | 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 | 2026-02-26T21:22:51Z | <!-- 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. -->
# Llama-3.3-70B-Instruct-3d-1M-100K-0.2-reverse-padzero-plus-mul-sub-99-512D-1L-2H-2048I
This model is a fine-tuned version of [met... | [] |
n1x-ax/flux-glasses-vton | n1x-ax | 2025-02-18T13:06:31Z | 0 | 7 | null | [
"vton",
"flux",
"lora",
"try-on",
"glasses",
"base_model:black-forest-labs/FLUX.1-Fill-dev",
"base_model:adapter:black-forest-labs/FLUX.1-Fill-dev",
"license:mit",
"region:us"
] | null | 2025-02-18T12:46:36Z | ### Flux Glasses Virtual Try-On (Beta) • ComfyUI
This early research beta workflow explores AI-driven virtual glasses try-on, combining LoRA fine-tuning, ControlNet inpainting, and latent space processin... | [] |
AfriScience-MT/nllb_200_distilled_600m-eng-zul | AfriScience-MT | 2026-02-04T16:55:26Z | 4 | 0 | null | [
"safetensors",
"m2m_100",
"translation",
"african-languages",
"scientific-translation",
"afriscience-mt",
"nllb",
"en",
"zu",
"dataset:afriscience-mt",
"base_model:facebook/nllb-200-distilled-600M",
"base_model:finetune:facebook/nllb-200-distilled-600M",
"license:apache-2.0",
"model-index"... | translation | 2026-02-04T16:54:39Z | # nllb_200_distilled_600m-eng-zul
[](https://huggingface.co/AfriScience-MT/nllb_200_distilled_600m-eng-zul)
This model is part of the **AfriScience-MT** project, focused on machine translation of scientific texts for African... | [] |
nlee-208/limo_S-dsr1b_T-q32b_50 | nlee-208 | 2025-08-11T05:19:23Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"text-generation-inference",
"endpoints... | text-generation | 2025-08-11T04:17:23Z | # Model Card for limo_S-dsr1b_T-q32b_50
This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
... | [] |
Hyeongwon/P2-split2_prob_Qwen3-8B-Base_0325-04-bs128-lr1e-5-epoch6 | Hyeongwon | 2026-03-27T15:26:25Z | 473 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:ChuGyouk/Qwen3-8B-Base",
"base_model:finetune:ChuGyouk/Qwen3-8B-Base",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-26T04:46:53Z | # Model Card for P2-split2_prob_Qwen3-8B-Base_0325-04-bs128-lr1e-5-epoch6
This model is a fine-tuned version of [ChuGyouk/Qwen3-8B-Base](https://huggingface.co/ChuGyouk/Qwen3-8B-Base).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
que... | [] |
isemmanuelolowe/Qwen3.6-35B-A3B-heretic | isemmanuelolowe | 2026-04-18T23:49:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5_moe",
"image-text-to-text",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-18T23:32:47Z | # This is a decensored version of [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 34.28 |
| **attn.o_proj.max_weight** | 1.20 |
| **attn.o_p... | [] |
hyun5ooo/mdeberta-v3-base-kor-further-ai-detect | hyun5ooo | 2025-11-09T17:17:11Z | 0 | 0 | null | [
"safetensors",
"deberta-v2",
"ai",
"detect",
"text-classification",
"ko",
"base_model:lighthouse/mdeberta-v3-base-kor-further",
"base_model:finetune:lighthouse/mdeberta-v3-base-kor-further",
"license:mit",
"region:us"
] | text-classification | 2025-10-08T12:04:42Z | #### mdeberta-v3-base-ko-further-ai-detect
Model Details
[2025 SW중심대학 디지털 경진대회 : AI부문 : 생성형 AI(LLM)와 인간 : 텍스트 판별 챌린지](https://dacon.io/competitions/official/236473) 수상작
이 모델은 한성대학교 SW중심대학사업단으로부터 후원 받은 Cloud GPU 로 학습되었습니다.
How to Get Started with the Model
```python
from transformers import AutoTokenizer, Aut... | [] |
miromind-ai/MiroThinker-v1.5-30B | miromind-ai | 2026-03-20T08:20:28Z | 973 | 244 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"agent",
"open-source",
"miromind",
"deep-research",
"conversational",
"en",
"arxiv:2511.11793",
"base_model:Qwen/Qwen3-30B-A3B-Thinking-2507",
"base_model:finetune:Qwen/Qwen3-30B-A3B-Thinking-2507",
"license:mit",
"eval-resu... | text-generation | 2026-01-04T05:49:36Z | <div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/68525b342230a897a65cc1c0/87mYQ_a-4jpnMkVR4hrgm.png" width="55%" alt="MiroThinker" />
</div>
<div align="center">
[](https://dr.m... | [] |
84basi/lora-5-32 | 84basi | 2026-02-14T10:33:45Z | 1 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:unsloth/Qwen3-4B-Instruct-2507",
"base_model:adapter:unsloth/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-14T10:33:26Z | qwen3-4b-structured-output-lora
This repository provides a **LoRA adapter** fine-tuned from
**unsloth/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 ... | [
{
"start": 95,
"end": 102,
"text": "unsloth",
"label": "training method",
"score": 0.8805282711982727
},
{
"start": 136,
"end": 141,
"text": "QLoRA",
"label": "training method",
"score": 0.8353461623191833
},
{
"start": 539,
"end": 546,
"text": "unsloth",
... |
JANGQ-AI/MiniMax-M2.5-JANG_3L | JANGQ-AI | 2026-03-25T02:29:13Z | 43 | 0 | mlx | [
"mlx",
"safetensors",
"minimax_m2",
"jang",
"quantized",
"mixed-precision",
"apple-silicon",
"reasoning",
"thinking",
"moe",
"text-generation",
"conversational",
"custom_code",
"en",
"zh",
"ja",
"ko",
"base_model:MiniMaxAI/MiniMax-M2.5",
"base_model:quantized:MiniMaxAI/MiniMax-M2... | text-generation | 2026-03-25T02:05:39Z | <p align="center">
<a href="https://mlx.studio"><img src="https://raw.githubusercontent.com/jjang-ai/jangq/main/assets/mlx-studio-light.png" alt="MLX Studio" width="500"></a>
</p>
<h4 align="center"><a href="https://mlx.studio">MLX Studio</a> — native JANG support with reasoning</h4>
---
<p align="center">
<img ... | [] |
Mardiyyah/variant-tapt_ulmfit_whole_word-LR_2e-05 | Mardiyyah | 2025-11-21T10:32:43Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"fill-mask",
"generated_from_trainer",
"en",
"dataset:Mardiyyah/TAPT-PDBE-V1",
"base_model:microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext",
"base_model:finetune:microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext",
"license:apache-2.0... | fill-mask | 2025-11-21T10:00:07Z | <!-- 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. -->
# variant-tapt_ulmfit_whole_word-LR_2e-05
This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstra... | [] |
jeongjoonhyeok/HY-MT1.5-7B-mlx-4Bit | jeongjoonhyeok | 2026-01-01T08:02:05Z | 19 | 0 | transformers | [
"transformers",
"safetensors",
"hunyuan_v1_dense",
"text-generation",
"translation",
"mlx",
"mlx-my-repo",
"zh",
"en",
"fr",
"pt",
"es",
"ja",
"tr",
"ru",
"ar",
"ko",
"th",
"it",
"de",
"vi",
"ms",
"id",
"tl",
"hi",
"pl",
"cs",
"nl",
"km",
"my",
"fa",
"gu... | translation | 2026-01-01T08:01:40Z | # jeongjoonhyeok/HY-MT1.5-7B-mlx-4Bit
The Model [jeongjoonhyeok/HY-MT1.5-7B-mlx-4Bit](https://huggingface.co/jeongjoonhyeok/HY-MT1.5-7B-mlx-4Bit) was converted to MLX format from [tencent/HY-MT1.5-7B](https://huggingface.co/tencent/HY-MT1.5-7B) using mlx-lm version **0.28.3**.
## Use with mlx
```bash
pip install mlx... | [] |
1990two/mobius_markov | 1990two | 2025-08-20T07:01:23Z | 0 | 0 | pytorch | [
"pytorch",
"markov-chains",
"complex-analysis",
"non-euclidean-geometry",
"classics-revival",
"experimental",
"license:apache-2.0",
"region:us"
] | null | 2025-08-18T19:08:54Z | # Möbius Markov Chain - The Classics Revival
**Non-Euclidean Probabilistic Systems with Dynamic Geometry**
**Experimental Research Code** - Functional but unoptimized, expect rough edges
## What Is This?
Möbius Markov Chain operates Markov processes in complex space with dynamically warped geometry via Möbius trans... | [] |
aisingapore/Qwen-SEA-LION-v4-32B-IT | aisingapore | 2026-05-04T12:35:29Z | 7,123 | 7 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"en",
"zh",
"vi",
"id",
"th",
"fil",
"ta",
"ms",
"km",
"lo",
"my",
"arxiv:2502.14301",
"arxiv:2311.07911",
"arxiv:2306.05685",
"base_model:Qwen/Qwen3-32B",
"base_model:finetune:Qwen/Qwen3-32B",
"te... | text-generation | 2025-10-16T06:58:34Z | 
## Qwen-SEA-LION-v4-32B-IT (Instruct model)
Last update: 2025-10-16
SEA-LION is a collection of Large Language Models (LLMs) which have been pretrained and instruct-tuned for the Southeast Asia (SEA) region.
**Qwen-SEA-LION-v4-32B-IT** is based on Qwen3, which... | [] |
patrickamadeus/momh-2k1img-step-nopack-cont3000-600 | patrickamadeus | 2026-02-17T06:38:42Z | 0 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"research",
"image-text-to-text",
"license:mit",
"region:us"
] | image-text-to-text | 2026-02-17T06:37:39Z | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
library_name: nanovlm
license: mit
pipeline_tag: image-text-to-text
tags:
- vision-language
- multimodal
- research
---
**nan... | [] |
g-assismoraes/Qwen3-4B-CCC-adapters | g-assismoraes | 2026-01-22T09:08:43Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-4B-Base",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-4B-Base",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-01-18T15:37:58Z | <!-- 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. -->
# Qwen3-4B-CCC-adapters
This model is a fine-tuned version of [Qwen/Qwen3-4B-Base](https://huggingface.co/Qwen/Qwen3-4B-Base) on an... | [] |
Nabi400/lstm_forecaster | Nabi400 | 2025-10-03T14:05:37Z | 0 | 0 | null | [
"time-series",
"forecasting",
"sales",
"lstm",
"arima",
"en",
"dataset:custom",
"license:mit",
"region:us"
] | null | 2025-10-03T13:39:45Z | # 📈 Retail Sales Forecasting with ARIMA and LSTM
## Model Details
This project compares two forecasting approaches for retail sales prediction:
- **ARIMA (AutoRegressive Integrated Moving Average)**
- **LSTM (Long Short-Term Memory neural network)**
The models were trained and evaluated using a **rolling window eval... | [] |
Cyberbrainiac/act_so101_sucker_5ksteps | Cyberbrainiac | 2025-12-20T23:02:30Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:Cyberbrainiac/record-test",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-20T23:02:20Z | # 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":... |
amoozeshyar/amoozeshyar-beta-0.3-alpaca | amoozeshyar | 2025-08-25T16:09:12Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"fa",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-08-25T15:37:31Z | # Amoozeshyar (Beta)
## Model Description
Amoozeshyar is a Persian educational AI assistant designed to help students learn in a simple and supportive way. Based on **Qwen2.5-7B-Instruct**, it provides child-friendly tutoring, motivational responses, and clear explanations for school subjects.
---
## Intended Use
**... | [] |
zainabdah/MLOps-Course-M2 | zainabdah | 2025-09-02T11:24:01Z | 1 | 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 | 2025-09-02T11:19:35Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# MLOps-Course-M2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) o... | [] |
Koba-8Tarku/lora_structeval_t_qwen3_4b_TK1-3g | Koba-8Tarku | 2026-02-08T12:53:27Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v5",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-08T12:21:48Z | qwen3-4b-structured-output-lora_TK1-3g
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 impr... | [
{
"start": 140,
"end": 145,
"text": "QLoRA",
"label": "training method",
"score": 0.7919551134109497
}
] |
JonusNattapong/xauusd-scalping-models | JonusNattapong | 2025-10-22T09:06:32Z | 0 | 5 | null | [
"joblib",
"region:us"
] | null | 2025-10-22T06:19:01Z | <!-- ---
license: mit
tags:
- trading
- finance
- forex
- xauusd
- gold
- scalping
- machine-learning
- deep-learning
- lstm
- transformer
- xgboost
- ensemble
- quantitative-finance
- algorithmic-trading
datasets:
- ZombitX64/xauusd-gold-price-historical-data-2004-2025
... | [] |
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