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 |
|---|---|---|---|---|---|---|---|---|---|---|
fariasultanacodes/magic | fariasultanacodes | 2025-11-17T06:09:57Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation",
"magic",
"mmlu",
"causal-lm",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-1.5B",
"base_model:finetune:Qwen/Qwen2.5-1.5B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-17T05:42:58Z | # Magic Model 🪄
Fine-tuned language model for MMLU-style question answering.
**Developed by Likhon Sheikh** 🚀
## Features
- ✅ Multi-safetensor support
- ✅ Fast tokenizer with tokenizer.json
- ✅ LoRA fine-tuning for efficiency
- ✅ MMLU-optimized responses
- ✅ Production-ready deployment
## Usage
```python
from t... | [] |
feabries/dog_dreambooth_model_prior | feabries | 2026-03-04T09:54:51Z | 12 | 0 | diffusers | [
"diffusers",
"tensorboard",
"safetensors",
"text-to-image",
"dreambooth",
"diffusers-training",
"stable-diffusion",
"stable-diffusion-diffusers",
"base_model:CompVis/stable-diffusion-v1-4",
"base_model:finetune:CompVis/stable-diffusion-v1-4",
"license:creativeml-openrail-m",
"endpoints_compati... | text-to-image | 2026-03-04T08:58:31Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - feabries/dog_dreambooth_model_prior
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. ... | [
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"end": 209,
"text": "DreamBooth",
"label": "training method",
"score": 0.9621815085411072
},
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"end": 269,
"text": "dreambooth",
"label": "training method",
"score": 0.9596779346466064
},
{
"start": 374,
"end": 384,
"text": "D... |
tiiuae/Falcon-H1-Tiny-R-0.6B-GGUF | tiiuae | 2026-01-21T19:37:19Z | 496 | 8 | transformers | [
"transformers",
"gguf",
"falcon-h1",
"edge",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-13T06:53:58Z | <img src="https://cdn-uploads.huggingface.co/production/uploads/62441d1d9fdefb55a0b7d12c/l1du02RjuAZJcksI5tQ-F.png" alt="drawing" width="800"/>
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Training Details](#training-details)
3. [Usage](#usage)
4. [Evaluation](#evaluation)
5. [Citati... | [] |
mradermacher/concise-cbt-therapist-qwen3-1.7b-i1-GGUF | mradermacher | 2026-01-28T14:46:11Z | 11 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:therapygym/concise-cbt-therapist-qwen3-1.7b",
"base_model:quantized:therapygym/concise-cbt-therapist-qwen3-1.7b",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-28T13:43:57Z | ## 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_... | [] |
AlignmentResearch/obfuscation-atlas-Meta-Llama-3-8B-Instruct-kl0.01-det1-seed3-deception_probe | AlignmentResearch | 2026-02-20T21:59:27Z | 0 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"model-type:honest",
"arxiv:2602.15515",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:mit",
"region:us"
] | null | 2026-02-17T10:05:12Z | # RLVR-trained policy from The Obfuscation Atlas
This is a policy trained on MBPP-Honeypot with deception probes,
from the [Obfuscation Atlas paper](https://arxiv.org/abs/2602.15515),
uploaded for reproducibility and further research.
The training code and RL environment are available at: https://github.com/Alignment... | [] |
mlx-community/MiroThinker-1.7-mini-mlx-4Bit | mlx-community | 2026-03-15T23:37:40Z | 143 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"agent",
"open-source",
"miromind",
"deep-research",
"mlx",
"mlx-my-repo",
"conversational",
"en",
"base_model:miromind-ai/MiroThinker-1.7-mini",
"base_model:quantized:miromind-ai/MiroThinker-1.7-mini",
"license:apache-2.0",
... | text-generation | 2026-03-15T23:35:57Z | # cbalgeman/MiroThinker-1.7-mini-mlx-4Bit
The Model [cbalgeman/MiroThinker-1.7-mini-mlx-4Bit](https://huggingface.co/cbalgeman/MiroThinker-1.7-mini-mlx-4Bit) was converted to MLX format from [miromind-ai/MiroThinker-1.7-mini](https://huggingface.co/miromind-ai/MiroThinker-1.7-mini) using mlx-lm version **0.29.1**.
##... | [] |
gumperto/Llama-3.2-1B-Instruct-emergent-finetune-tests_samples-down-l8-r1 | gumperto | 2025-09-18T00:19:42Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"unsloth",
"conversational",
"base_model:unsloth/Llama-3.2-1B-Instruct",
"base_model:finetune:unsloth/Llama-3.2-1B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
... | text-generation | 2025-09-18T00:08:43Z | # Model Card for Llama-3.2-1B-Instruct-emergent-finetune-tests_samples-down-l8-r1
This model is a fine-tuned version of [unsloth/Llama-3.2-1B-Instruct](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformer... | [] |
StefanWagnerWandelbots/pusht_keyboard_policy_100k_100 | StefanWagnerWandelbots | 2026-01-19T22:24:18Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:StefanWagnerWandelbots/pusht_keyboard_15fps",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-19T22:24:02Z | # 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":... |
openpecha/BoKenlm-syl-v0.4 | openpecha | 2026-04-13T09:50:43Z | 0 | 0 | null | [
"region:us"
] | null | 2026-04-13T09:47:51Z | # BoKenlm-syl-v0.4 - Tibetan KenLM Language Model
A KenLM n-gram language model trained on Tibetan text, tokenized with syllable tokenizer.
## Model Details
| Parameter | Value |
| --- | --- |
| **Model Type** | Modified Kneser-Ney 5-gram |
| **Tokenizer** | Tibetan syllable-based (botok-rs SimpleTokenizer) |
| **Tr... | [] |
OpenMed/privacy-filter-multilingual-mlx-8bit | OpenMed | 2026-05-04T10:54:25Z | 0 | 1 | openmed | [
"openmed",
"openai_privacy_filter",
"mlx",
"apple-silicon",
"token-classification",
"pii",
"de-identification",
"privacy-filter",
"multilingual",
"ar",
"bn",
"de",
"en",
"es",
"fr",
"hi",
"it",
"ja",
"ko",
"nl",
"pt",
"te",
"tr",
"vi",
"zh",
"dataset:ai4privacy/pii-... | token-classification | 2026-05-03T21:09:50Z | # OpenMed Privacy Filter (Multilingual) — MLX 8-bit
A native [MLX](https://github.com/maziyarpanahi/openmed/) port of
[`OpenMed/privacy-filter-multilingual`](https://huggingface.co/OpenMed/privacy-filter-multilingual)
for fast, on-device fine-grained PII detection across **54 categories**
and **16 languages** on Apple... | [] |
Leoinhouse/ImagineClassification-finetuned-model | Leoinhouse | 2026-03-27T07:01:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-classification",
"vision",
"fashion",
"ecommerce",
"dataset:ashraq/fashion-product-images-small",
"base_model:google/vit-base-patch16-224-in21k",
"base_model:finetune:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"endpoints_compatible",
... | image-classification | 2026-03-27T05:26:12Z | # ImagineClassification (fine-tuned ViT)
Fine-tuned **Vision Transformer (ViT-B/16, patch 16, 224×224)** for **coarse fashion product classification** into four `masterCategory` labels from the [Fashion Product Images (small)](https://huggingface.co/datasets/ashraq/fashion-product-images-small) dataset.
## Model summ... | [] |
DJLougen/Ornstein-27B-GGUF | DJLougen | 2026-04-09T21:37:53Z | 1,227 | 8 | null | [
"gguf",
"reasoning",
"qwen3.5",
"ddm",
"llama-cpp",
"quantized",
"image-text-to-text",
"en",
"base_model:DJLougen/Ornstein-27B",
"base_model:quantized:DJLougen/Ornstein-27B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2026-04-07T23:25:31Z | # Ornstein-27B-GGUF
GGUF quantizations of [DJLougen/Ornstein-27B](https://huggingface.co/DJLougen/Ornstein-27B) — a reasoning-focused fine-tune of Qwen 3.5 27B trained on **1,229 high-quality reasoning traces** curated through a custom **Drift Diffusion Modeling (DDM)** pipeline.
## Support This Work
I'm a P... | [] |
leonat3t/collapse_qwen2-0.5b_hs2_replace_iter1_sftsd0 | leonat3t | 2026-02-10T07:42:56Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"trl",
"sft",
"generated_from_trainer",
"base_model:Qwen/Qwen2-0.5B",
"base_model:finetune:Qwen/Qwen2-0.5B",
"license:apache-2.0",
"region:us"
] | null | 2026-02-09T10:59:14Z | <!-- 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. -->
# collapse_qwen2-0.5b_hs2_replace_iter1_sftsd0
This model is a fine-tuned version of [Qwen/Qwen2-0.5B](https://huggingface.co/Qwen/... | [] |
bjorndev/recita-dialogue-identifier | bjorndev | 2025-11-27T21:05:13Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:finetune:meta-llama/Meta-Llama-3-8B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-11-26T17:45:54Z | # Model Card for recita-dialogue-identifier
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
questio... | [] |
Khanbby/HunyuanVideo | Khanbby | 2026-03-04T06:06:14Z | 9 | 1 | null | [
"text-to-video",
"arxiv:2412.03603",
"arxiv:2405.07719",
"license:other",
"region:us"
] | text-to-video | 2026-03-04T06:06:13Z | <!-- ## **HunyuanVideo** -->
<p align="center">
<img src="https://raw.githubusercontent.com/Tencent/HunyuanVideo/refs/heads/main/assets/logo.png" height=100>
</p>
# HunyuanVideo: A Systematic Framework For Large Video Generation Model Training
-----
This repo contains PyTorch model definitions, pre-trained weigh... | [] |
Thireus/GLM-4.7-THIREUS-IQ4_NL-SPECIAL_SPLIT | Thireus | 2026-02-12T08:55:58Z | 0 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-02T08:39:45Z | # GLM-4.7
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/GLM-4.7-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the GLM-4.7 model (official repo: https://huggingface.co/zai-org/GLM-4.7). These GGUF shards are designed to be used with **Thireus’ ... | [] |
BilateralBusiness/perma_chef_filipina_caribe_verde_menta_hombre_4_20251001_1719 | BilateralBusiness | 2025-10-02T22:36:03Z | 2 | 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 | 2025-10-02T22:22:33Z | # Perma_Chef_Filipina_Caribe_Verde_Menta_Hombre_4_20251001_1719
<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 toolk... | [] |
franzhanz/pythia-70m-deduped-finetuned-NYT | franzhanz | 2025-11-27T02:54:04Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-70m-deduped",
"base_model:finetune:EleutherAI/pythia-70m-deduped",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-27T02:52:39Z | <!-- 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. -->
# pythia-70m-deduped-finetuned-NYT
This model is a fine-tuned version of [EleutherAI/pythia-70m-deduped](https://huggingface.co/Ele... | [] |
Ignatfhc/Hhhhh | Ignatfhc | 2025-09-09T22:16:06Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-feature-extraction",
"endpoints_compatible",
"region:us"
] | image-feature-extraction | 2025-09-09T15:51:35Z | # Unified Hugging Face Model Repository
Este repositorio contiene una unificación de múltiples modelos.
## Modelos originales
- https://huggingface.co/huihui-ai/Huihui-gemma-3-270m-it-abliterated
- https://huggingface.co/Searchium-ai/clip4clip-webvid150k
- https://huggingface.co/caidas/swin2SR-lightweight-x2-64
- htt... | [] |
mradermacher/Talkia_FP16-GGUF | mradermacher | 2025-08-25T19:31:44Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:ShihteSiao/Talkia_FP16",
"base_model:quantized:ShihteSiao/Talkia_FP16",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-25T18:46:39Z | ## 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... | [] |
ZhengPeng7/BiRefNet_lite | ZhengPeng7 | 2026-02-04T22:43:46Z | 31,862 | 16 | birefnet | [
"birefnet",
"safetensors",
"background-removal",
"mask-generation",
"Dichotomous Image Segmentation",
"Camouflaged Object Detection",
"Salient Object Detection",
"pytorch_model_hub_mixin",
"model_hub_mixin",
"image-segmentation",
"custom_code",
"arxiv:2401.03407",
"endpoints_compatible",
"... | image-segmentation | 2024-08-02T03:51:45Z | <h1 align="center">Bilateral Reference for High-Resolution Dichotomous Image Segmentation</h1>
<div align='center'>
<a href='https://scholar.google.com/citations?user=TZRzWOsAAAAJ' target='_blank'><strong>Peng Zheng</strong></a><sup> 1,4,5,6</sup>, 
<a href='https://scholar.google.com/citations?user=0uP... | [] |
soda-research/discrete-audio-isoflop-9e19-851M-d1408-L14-B128-1016c0 | soda-research | 2026-02-13T17:29:06Z | 1 | 0 | null | [
"safetensors",
"qwen3",
"audio",
"speech",
"foundation-model",
"next-token-prediction",
"isoflop",
"research",
"license:apache-2.0",
"region:us"
] | null | 2026-02-10T09:38:39Z | # Discrete Audio IsoFLOP Model (discrete-audio-isoflop-9e19-851M-d1408-L14-B128-1016c0)
A suite of discrete audio models trained for our IsoFLOP study as part of **SODA**, which is a unified next-token prediction on interleaved semantic, acoustic, and text tokens.
🥤 **Project Page:** [https://soda-audio.github.io](... | [] |
Zyoung203/Qwen3-Embedding-0.6B-PPO | Zyoung203 | 2025-09-11T09:28:32Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"dataset:nq_hotpotqa_train",
"arxiv:1909.08593",
"base_model:Qwen/Qwen3-Embedding-0.6B",
"base_model:finetune:Qwen/Qwen3-Embedding-0.6B",
"endpoints_compatible",
"region:us"
] | null | 2025-08-26T08:25:22Z | # Model Card for Qwen3-Embedding-0.6B-PPO
This model is a fine-tuned version of [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B) on the [nq_hotpotqa_train](https://huggingface.co/datasets/nq_hotpotqa_train) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
## Q... | [] |
NeuML/txtai-arxiv | NeuML | 2026-04-20T17:04:44Z | 9 | 21 | txtai | [
"txtai",
"sentence-similarity",
"en",
"dataset:arxiv_dataset",
"license:cc0-1.0",
"region:us"
] | sentence-similarity | 2024-01-16T13:02:57Z | # arXiv txtai embeddings index
This is a [txtai](https://github.com/neuml/txtai) embeddings index for the [arXiv dataset](https://hf.co/datasets/arxiv_dataset) [metadata](https://info.arxiv.org/help/prep.html).
txtai must be [installed](https://neuml.github.io/txtai/install/) to use this model.
## Example
This inde... | [] |
mradermacher/MiniMax-M2.5-GGUF | mradermacher | 2026-02-21T17:25:18Z | 784 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:MiniMaxAI/MiniMax-M2.5",
"base_model:quantized:MiniMaxAI/MiniMax-M2.5",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-19T05:14:31Z | ## 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... | [] |
enguard/tiny-guard-4m-en-response-safety-multilabel-polyguard | enguard | 2025-11-03T13:46:40Z | 0 | 0 | model2vec | [
"model2vec",
"safetensors",
"static-embeddings",
"text-classification",
"dataset:ToxicityPrompts/PolyGuardMix",
"license:mit",
"region:us"
] | text-classification | 2025-11-01T17:44:17Z | # enguard/tiny-guard-4m-en-response-safety-multilabel-polyguard
This model is a fine-tuned Model2Vec classifier based on [minishlab/potion-base-4m](https://huggingface.co/minishlab/potion-base-4m) for the response-safety-multilabel found in the [ToxicityPrompts/PolyGuardMix](https://huggingface.co/datasets/ToxicityPro... | [] |
enacimie/WebSailor-3B-Q8_0-GGUF | enacimie | 2025-09-02T21:56:45Z | 4 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:Alibaba-NLP/WebSailor-3B",
"base_model:quantized:Alibaba-NLP/WebSailor-3B",
"license:apache-2.0",
"region:us"
] | null | 2025-09-02T21:56:30Z | # enacimie/WebSailor-3B-Q8_0-GGUF
This model was converted to GGUF format from [`Alibaba-NLP/WebSailor-3B`](https://huggingface.co/Alibaba-NLP/WebSailor-3B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface... | [] |
neural-interactive-proofs/finetune_dpo_qwen2_5-32b-instruct_cv_transfer_test_train_3_0_iter_0_provers_group_1754480628 | neural-interactive-proofs | 2025-08-06T11:55:52Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-32B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-06T11:55:09Z | # Model Card for finetune_dpo_qwen2_5-32b-instruct_cv_transfer_test_train_3_0_iter_0_provers_group_1754480628
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```pyt... | [] |
erranli/qwen2.5-7b-mot-grokking | erranli | 2025-09-25T00:32:38Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"qwen2",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-24T23:56:27Z | # Model Card for highq-mot-run0
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, bu... | [] |
lepao/act_so101_test | lepao | 2026-03-09T10:31:19Z | 123 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:lepao/so101_test",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-25T22:43:42Z | # 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":... |
arman1o1/bert-base-cased-wikitext2 | arman1o1 | 2025-12-16T05:50:31Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"fill-mask",
"generated_from_trainer",
"base_model:google-bert/bert-base-cased",
"base_model:finetune:google-bert/bert-base-cased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-12-16T05:31:50Z | <!-- 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. -->
# bert-base-cased-wikitext2
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an u... | [
{
"start": 256,
"end": 271,
"text": "bert-base-cased",
"label": "training method",
"score": 0.7640406489372253
}
] |
mradermacher/gemma-3-27b-it-heretic-GGUF | mradermacher | 2025-11-24T06:09:36Z | 247 | 1 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:coder3101/gemma-3-27b-it-heretic",
"base_model:quantized:coder3101/gemma-3-27b-it-heretic",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-23T23:19:34Z | ## 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... | [] |
Josephinepassananti/flux_taylor_tomlinson_ft_dataset_512_shaded_0.03_dog_captions_bs1_steps1500 | Josephinepassananti | 2025-12-03T03:43:42Z | 1 | 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 | 2025-12-03T02:38:47Z | <!-- 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 - Josephinepassananti/flux_taylor_tomlinson_ft_dataset_512_shaded_0.03_dog_captions_bs1_steps1500
<... | [] |
paulo037/20260501T233646Z-legal_extraction-graft-19faf2a5 | paulo037 | 2026-05-02T00:33:54Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-VL-2B-Instruct",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-VL-2B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-05-01T23:40:41Z | <!-- 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. -->
# 20260501T233646Z-legal_extraction-graft-19faf2a5
This model is a fine-tuned version of [Qwen/Qwen3-VL-2B-Instruct](https://huggin... | [] |
qualiaadmin/b9e2d7a1-cfda-4f2b-800d-59bb0ecde4c1 | qualiaadmin | 2026-01-14T16:20:58Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi0",
"dataset:DozenDucc/robot_pickup_dataset",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-14T16:19:53Z | # 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 ... | [] |
JakeOh/llada-1.0-s1 | JakeOh | 2026-01-12T13:40:56Z | 1 | 0 | peft | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:GSAI-ML/LLaDA-8B-Instruct",
"base_model:adapter:GSAI-ML/LLaDA-8B-Instruct",
"license:mit",
"region:us"
] | null | 2025-11-06T02:29:33Z | <!-- 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. -->
# llada-1.0-s1
This model is a fine-tuned version of [GSAI-ML/LLaDA-8B-Instruct](https://huggingface.co/GSAI-ML/LLaDA-8B-Instruct) ... | [] |
EvilScript/activation-oracle-gemma-4-E2B-it-step-60000 | EvilScript | 2026-04-13T16:59:42Z | 0 | 0 | peft | [
"peft",
"safetensors",
"gemma4",
"activation-oracles",
"interpretability",
"lora",
"self-introspection",
"sae",
"arxiv:2512.15674",
"base_model:google/gemma-4-E2B-it",
"base_model:adapter:google/gemma-4-E2B-it",
"license:apache-2.0",
"region:us"
] | null | 2026-04-13T16:59:10Z | # Activation Oracle: gemma-4-E2B-it
This is a **LoRA adapter** that turns [gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-it)
into an **activation oracle** -- an LLM that can read and interpret the internal
activations of other LLMs (or itself) in natural language.
## What is an activation oracle?
An acti... | [] |
abaryan/CyberXP_Agent_Llama_3.2_1B | abaryan | 2025-10-07T12:57:33Z | 23,187 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"SFT",
"rl",
"Cybersecurity",
"trl",
"conversational",
"en",
"dataset:AlicanKiraz0/Cybersecurity-Dataset-v1",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-1B-Instruct",
"license:mit",
"... | text-generation | 2025-10-07T11:10:27Z | # DrDiag-QwenVL2
CyberXP Agent: An AI-Powered Cyber Threat Assessment Solution
### Real-World Cyber Threat Assessment Made Simple with CyberXP Agent
Cybersecurity teams today are under constant pressure to detect and respond to threats quickly and accurately.
There’s no shortage of tools out there, but many require... | [] |
darkmaniac7/SmolLM2-1.7B-Instruct-MNN | darkmaniac7 | 2026-04-02T01:47:30Z | 0 | 0 | null | [
"mnn",
"llama",
"mobile",
"on-device",
"tokforge",
"uncensored",
"abliterated",
"text-generation",
"en",
"base_model:HuggingFaceTB/SmolLM2-1.7B-Instruct",
"base_model:finetune:HuggingFaceTB/SmolLM2-1.7B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-02T01:24:41Z | # SmolLM2-1.7B-Instruct-MNN
Pre-converted [SmolLM2 1.7B Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct) in MNN format for on-device inference with [TokForge](https://tokforge.ai).
> **Original model by [HuggingFace](https://huggingface.co/HuggingFace)** — converted to MNN Q4 for mobile deploymen... | [] |
antoniorv6/smt-grandstaff | antoniorv6 | 2024-09-07T07:42:53Z | 601 | 6 | null | [
"safetensors",
"SMT",
"omr",
"camera_grandstaff",
"image-to-text",
"dataset:antoniorv6/grandstaff",
"arxiv:2402.07596",
"license:mit",
"region:us"
] | image-to-text | 2024-08-13T08:16:26Z | # Sheet Music Transformer (base model, fine-tuned on the Grandstaff dataset)
The SMT model fine-tuned on the _Camera_ GrandStaff dataset for pianoform transcription.
The code of the model is hosted in [this repository](https://github.com/antoniorv6/SMT).
## Model description
The SMT model consists of a vision encode... | [] |
ekiprop/llama3-8b-quant-comp-stabilized | ekiprop | 2026-02-06T11:01:59Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3-8B",
"lora",
"transformers",
"text-generation",
"base_model:meta-llama/Meta-Llama-3-8B",
"license:llama3",
"region:us"
] | text-generation | 2026-02-06T08:06:52Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama3-8b-quant-comp-stabilized
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-ll... | [] |
mradermacher/Llama-3.3-8B-Casimir-v0.2-GGUF | mradermacher | 2026-03-07T02:41:54Z | 961 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"heretic",
"roleplay",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:0xA50C1A1/Llama-3.3-8B-Casimir-v0.2",
"base_model:quantized:0xA50C1A1/Llama-3.3-8B-Casimir-v0.2",
"license:llama3.3",
"endpoints_co... | null | 2026-03-04T01:58:22Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-v2-3d-4M-400K-0.1-reverse-padzero-99-64D-3L-4H-256I | arithmetic-circuit-overloading | 2026-04-05T06:04:11Z | 0 | 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 | 2026-04-04T08:46:27Z | <!-- 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. -->
# Llama-3.3-70B-Instruct-v2-3d-4M-400K-0.1-reverse-padzero-99-64D-3L-4H-256I
This model is a fine-tuned version of [meta-llama/Llam... | [] |
mlx-community/Ministral-3-14B-Reasoning-2512-6bit | mlx-community | 2025-12-04T01:03:09Z | 57 | 0 | vllm | [
"vllm",
"safetensors",
"mistral3",
"mistral-common",
"mlx",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"base_model:mistralai/Ministral-3-14B-Base-2512",
"base_model:quantized:mistralai/Ministral-3-14B-Base-2512",
"license:apache-2.0",
"6-bit",
"region:u... | null | 2025-12-04T00:59:06Z | # mlx-community/Ministral-3-14B-Reasoning-2512-6bit
This model was converted to MLX format from [`mistralai/Ministral-3-14B-Reasoning-2512`]() using mlx-vlm version **0.3.9**.
Refer to the [original model card](https://huggingface.co/mistralai/Ministral-3-14B-Reasoning-2512) for more details on the model.
## Use with m... | [] |
chanc031965/Tesla_Detection | chanc031965 | 2026-03-25T13:06:05Z | 19 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-classification",
"binary-classification",
"base_model:zjs81/Electric-Car-Brand-Classifier",
"base_model:finetune:zjs81/Electric-Car-Brand-Classifier",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2026-03-21T05:44:56Z | # Tesla Binary Image Classifier
A fine-tuned image classification model that answers one question:
**Is this car a Tesla? (Yes / No)**
## Model Description
This model is fine-tuned from
[zjs81/Electric-Car-Brand-Classifier](https://huggingface.co/zjs81/Electric-Car-Brand-Classifier)
on a custom Tesla vs. Not Tesla... | [
{
"start": 695,
"end": 722,
"text": "Binary Image Classification",
"label": "training method",
"score": 0.7529432773590088
}
] |
HangZhengPKU/Self-Assembling-Amyloid-Like-Peptides-Predictor | HangZhengPKU | 2025-12-06T10:54:17Z | 0 | 0 | null | [
"arxiv:2303.16982",
"license:cc-by-nc-nd-4.0",
"region:us"
] | null | 2025-12-06T08:18:06Z | # unimol tools for various prediction and downstreams.
Documentation of Uni-Mol tools is available at https://unimol.readthedocs.io/en/latest/
## details can be found in bohrium notebook
* [unimol property predict](https://bohrium.dp.tech/notebook/298bcead4f614971bb62fbeef2e9db16)
* [unimol representation](https://bo... | [] |
amps93/qwen3-tts-finetune-korean-woman-v6-epoch-3 | amps93 | 2026-03-18T05:12:52Z | 27 | 0 | null | [
"safetensors",
"qwen3_tts",
"arxiv:2601.15621",
"license:apache-2.0",
"region:us"
] | null | 2026-03-18T05:12:25Z | # Qwen3-TTS
## Overview
### Introduction
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_introduction.png" width="90%"/>
<p>
Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as... | [] |
mrm8488/t5-small-finetuned-text-simplification | mrm8488 | 2022-09-15T05:48:36Z | 98 | 2 | transformers | [
"transformers",
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:wiki_auto_asset_turk",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2022-09-14T23:34:15Z | <!-- 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. -->
# t5-small-finetuned-text-simplification
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the w... | [] |
TheCluster/GLM-4.6V-Flash-Heretic-MLX-mxfp4 | TheCluster | 2026-02-27T01:34:09Z | 318 | 0 | mlx | [
"mlx",
"safetensors",
"glm4v",
"heretic",
"uncensored",
"unrestricted",
"decensored",
"abliterated",
"mxfp4",
"image-text-to-text",
"conversational",
"en",
"zh",
"base_model:AiAsistent/GLM-4.6V-Flash-heretic",
"base_model:quantized:AiAsistent/GLM-4.6V-Flash-heretic",
"license:mit",
"... | image-text-to-text | 2026-02-25T19:11:39Z | <div align="center">
<img src=https://raw.githubusercontent.com/zai-org/GLM-V/refs/heads/main/resources/logo.svg width="40%"/>
</div>
# GLM-4.6V-Flash Heretic MLX mxfp4
# This is a decensored version of [zai-org/GLM-4.6V-Flash](https://huggingface.co/zai-org/GLM-4.6V-Flash), made using [Heretic](https://github.com/p-... | [] |
hardlyworking/Qwen3-32B-biprojected-norm-preserving-abliterated-Q4_K_M-GGUF | hardlyworking | 2026-02-02T02:13:55Z | 22 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:vprilepskii/Qwen3-32B-biprojected-norm-preserving-abliterated",
"base_model:quantized:vprilepskii/Qwen3-32B-biprojected-norm-preserving-abliterated",
"endpoints_compatible",
"region:us"
] | null | 2026-02-02T02:11:17Z | # hardlyworking/Qwen3-32B-biprojected-norm-preserving-abliterated-Q4_K_M-GGUF
This model was converted to GGUF format from [`vprilepskii/Qwen3-32B-biprojected-norm-preserving-abliterated`](https://huggingface.co/vprilepskii/Qwen3-32B-biprojected-norm-preserving-abliterated) using llama.cpp via the ggml.ai's [GGUF-my-re... | [] |
mradermacher/GRM2-3b-i1-GGUF | mradermacher | 2026-05-01T11:33:05Z | 3,153 | 2 | transformers | [
"transformers",
"gguf",
"reasoning",
"coding",
"math",
"science",
"agent",
"tools",
"en",
"base_model:OrionLLM/GRM2-3b",
"base_model:quantized:OrionLLM/GRM2-3b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-21T05:04:30Z | ## 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_... | [] |
mradermacher/SFT-MedLLama-13B-GGUF | mradermacher | 2025-12-08T17:07:51Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:ik-ram28/SFT-MedLLama-13B",
"base_model:quantized:ik-ram28/SFT-MedLLama-13B",
"endpoints_compatible",
"region:us"
] | null | 2025-12-08T16:27:06Z | ## 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... | [] |
Carnot-EBM/constraint-propagation-logic | Carnot-EBM | 2026-04-11T15:32:26Z | 0 | 0 | null | [
"safetensors",
"ising_constraint_model",
"energy-based-model",
"ising-model",
"constraint-satisfaction",
"logic-verification",
"syllogism",
"carnot",
"license:apache-2.0",
"region:us"
] | null | 2026-04-11T15:32:23Z | > **Research Artifact — Not Production-Ready**
>
> This model verifies logical syllogism responses using structural binary features.
> It achieves AUROC 1.0 on the held-out test set (matching Exp 89 reference).
> It handles modus ponens, modus tollens, disjunctive syllogism, and affirming
> the consequent — not arbitra... | [
{
"start": 466,
"end": 503,
"text": "discriminative Contrastive Divergence",
"label": "training method",
"score": 0.756450355052948
},
{
"start": 987,
"end": 999,
"text": "modus ponens",
"label": "training method",
"score": 0.7299023866653442
},
{
"start": 1108,
... |
yonseiaie/my_awesome_qa_model | yonseiaie | 2025-11-13T05:05:27Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"question-answering",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | question-answering | 2025-11-13T04:33:13Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_qa_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/... | [] |
Shimajiri/mistral-finetuned-alpaca | Shimajiri | 2025-10-21T05:55:47Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1",
"base_model:finetune:tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1",
"endpoints_compatible",
"region:us"
] | null | 2025-10-15T07:47:15Z | # Model Card for mistral-finetuned-alpaca
This model is a fine-tuned version of [tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers impo... | [] |
arianaazarbal/qwen3-4b-20260213_182423_lc_rh_sot_recon_gen_lhext_t-d32540-step60 | arianaazarbal | 2026-02-13T19:49:14Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-02-13T19:48:30Z | # qwen3-4b-20260213_182423_lc_rh_sot_recon_gen_lhext_t-d32540-step60
## Experiment Info
- **Full Experiment Name**: `20260213_182423_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_recontextualization_gen_loophole_extension_train_loophole_extension_oldlp_training_seed1`
- **Short Name**: `20260213_182423_lc_... | [] |
AHegai/pi0_green-white-cubes | AHegai | 2026-01-05T20:04:25Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi0",
"dataset:AHegai/green-white-cubes-combined",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-05T20:00:38Z | # 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 ... | [] |
Muapi/sketch-art | Muapi | 2025-08-22T11:17:42Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-22T11:17:25Z | # Sketch Art
**Base model**: Flux.1 D
**Trained words**: sketch_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 = {"Content-Type":... | [] |
s3y/op-test | s3y | 2025-09-24T11:24:32Z | 0 | 0 | null | [
"safetensors",
"endpoints_compatible",
"region:us"
] | null | 2025-09-24T11:19:10Z | # openpi
openpi holds open-source models and packages for robotics, published by the [Physical Intelligence team](https://www.physicalintelligence.company/).
Currently, this repo contains three types of models:
- the [π₀ model](https://www.physicalintelligence.company/blog/pi0), a flow-based vision-language-action mo... | [] |
sam522/ppo-lunarlander-v3 | sam522 | 2025-08-22T19:09:46Z | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"LunarLander-v3",
"ppo",
"deep-reinforcement-learning",
"reinforcement-learning",
"region:us"
] | reinforcement-learning | 2025-08-22T19:09:41Z | # PPO Agent playing LunarLander-v3
This is a **PPO** agent trained on the **LunarLander-v3** environment.
## Usage
```python
import torch
import gymnasium as gym
from pathlib import Path
# Load the model
checkpoint = torch.load("model.pth")
network = Network(config) # You need to define the Network class
network.l... | [] |
jusiro2/DLILP_CMP | jusiro2 | 2025-11-25T10:59:34Z | 2 | 0 | null | [
"safetensors",
"model_hub_mixin",
"pytorch_model_hub_mixin",
"arxiv:2504.05227",
"license:mit",
"region:us"
] | null | 2025-11-24T16:12:04Z | ## A Reality Check of Vision-Language Pre-training in Radiology: Have We Progressed Using Text?
- Code: [DLILP](https://github.com/jusiro/DLILP)
- Paper: [IPMI 2025](https://link.springer.com/chapter/10.1007/978-3-031-96625-5_20) - [ArXiv](https://arxiv.org/abs/2504.05227)
- Docs: [Documentation](https://github.com/ju... | [
{
"start": 106,
"end": 111,
"text": "DLILP",
"label": "training method",
"score": 0.8516146540641785
},
{
"start": 139,
"end": 144,
"text": "DLILP",
"label": "training method",
"score": 0.8139822483062744
},
{
"start": 325,
"end": 330,
"text": "DLILP",
... |
fpadovani/goldfish_turkish_10mb | fpadovani | 2026-04-22T19:57:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"base_model:goldfish-models/tur_latn_10mb",
"base_model:finetune:goldfish-models/tur_latn_10mb",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-22T17:39:51Z | # Model Card for goldfish_turkish_10mb
This model is a fine-tuned version of [goldfish-models/tur_latn_10mb](https://huggingface.co/goldfish-models/tur_latn_10mb).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a... | [] |
yungisimon/qwen_offonigiri_merge_linear_epoch_10 | yungisimon | 2026-01-28T17:59:07Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"MAM",
"memory-augmented",
"parametric-memory",
"en",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-01-28T17:56:32Z | # MAM (Memory As a Model) Fine-tuned Model
This model was trained using the MAM (Memory As a Model) framework, which uses a small model as parametric memory instead of traditional RAG's non-parametric datastore.
## Model Details
- **Base Model**: Qwen/Qwen2.5-14B-Instruct
- **Training Framework**: MAM (Memory As a M... | [] |
yash-sawant22/stu_synthetic_combined_ggpt20b_t-oss-20b-v1_d1_b8_ga8_lr2e-04_e4 | yash-sawant22 | 2025-09-22T22:18:22Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:openai/gpt-oss-20b",
"base_model:finetune:openai/gpt-oss-20b",
"endpoints_compatible",
"region:us"
] | null | 2025-09-22T20:00:28Z | # Model Card for stu_synthetic_combined_ggpt20b_t-oss-20b-v1_d1_b8_ga8_lr2e-04_e4
This model is a fine-tuned version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
que... | [] |
UnifiedHorusRA/Landscape_Qwen | UnifiedHorusRA | 2025-09-10T06:00:18Z | 1 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-08T07:04:58Z | # Landscape [Qwen]
**Creator**: [nocor1i8](https://civitai.com/user/nocor1i8)
**Civitai Model Page**: [https://civitai.com/models/1893893](https://civitai.com/models/1893893)
---
This repository contains multiple versions of the 'Landscape [Qwen]' model from Civitai.
Each version's files, including a specific README... | [] |
xpiohealth/atlas-post-cutoff-9b-specialist | xpiohealth | 2026-04-20T02:48:14Z | 0 | 0 | peft | [
"peft",
"safetensors",
"lora",
"knowledge-injection",
"post-cutoff",
"atlas-architecture",
"base_model:Qwen/Qwen3.5-9B",
"base_model:adapter:Qwen/Qwen3.5-9B",
"license:apache-2.0",
"region:us"
] | null | 2026-04-20T02:45:59Z | # ATLAS Post-Cutoff Specialist (9B)
LoRA adapter (rank 64) for Qwen3.5-9B, gentle-trained on 103 QA pairs about Feb-Apr 2026 AI/ML research papers. Part of the ATLAS research architecture (bridge + specialist + text-level assembly for regulated domains).
## Training
- Base: Qwen/Qwen3.5-9B
- Data: 103 QA pair... | [] |
NotARoomba/eval_synapse_smvla | NotARoomba | 2025-12-21T07:13:04Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:NotARoomba/synapse",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-21T07:12:56Z | # 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... | [] |
plzsay/pick_up_the_cube_smolvla | plzsay | 2025-12-30T15:47:32Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:plzsay/pick_up_the_cube_aug",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-30T15:47:12Z | # 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... | [] |
Gidigi/gidigi_4d7f600c_0004 | Gidigi | 2026-02-21T18:38:15Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-02-21T12:36:15Z | <!-- 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. -->
# distilbert-base-uncased__hate_speech_offensive__train-32-2
This model is a fine-tuned version of [distilbert-base-uncased](https:... | [] |
acon96/Home-FunctionGemma-270m | acon96 | 2025-12-22T04:00:06Z | 510 | 3 | null | [
"safetensors",
"gguf",
"gemma3_text",
"automation",
"home",
"assistant",
"text-generation",
"conversational",
"en",
"de",
"es",
"fr",
"dataset:acon96/Home-Assistant-Requests-V2",
"base_model:google/functiongemma-270m-it",
"base_model:finetune:google/functiongemma-270m-it",
"license:gem... | text-generation | 2025-12-22T03:54:36Z | # Home-FunctionGemma-270m
The "Home" model is a fine tuning of the FunctionGemma model from Google. The model is able to control devices in the user's house via the "Assist" API, as well as perform basic question answering about the provided home's state.
The model is quantized using Lama.cpp in order to enable runni... | [] |
vividdream/Qwen-Open-Finance-R-8B-IQ4_NL-GGUF | vividdream | 2026-04-04T11:16:04Z | 0 | 1 | transformers | [
"transformers",
"gguf",
"finance",
"economics",
"business",
"question-answering",
"text-generation",
"financial-analysis",
"economic-modeling",
"business-intelligence",
"llama-cpp",
"gguf-my-repo",
"en",
"fr",
"de",
"base_model:DragonLLM/Qwen-Open-Finance-R-8B",
"base_model:quantized... | question-answering | 2026-04-04T11:15:37Z | # vividdream/Qwen-Open-Finance-R-8B-IQ4_NL-GGUF
This model was converted to GGUF format from [`DragonLLM/Qwen-Open-Finance-R-8B`](https://huggingface.co/DragonLLM/Qwen-Open-Finance-R-8B) 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 m... | [] |
bhargavvz/SkinGuard-AI | bhargavvz | 2026-03-13T17:37:36Z | 0 | 0 | null | [
"region:us"
] | null | 2026-03-13T17:27:30Z | <h1 align="center">🏥 SkinGuard AI</h1>
<h3 align="center">Production-Grade Skin Cancer Detection with Deep Learning</h3>
<p align="center">
<strong>EVA-02 + ConvNeXt-V2 + Swin-V2 Ensemble | ISIC 2019 | H100 Optimized</strong>
</p>
<p align="center">
<img src="https://img.shields.io/badge/PyTorch-2.2+-red?logo=py... | [] |
valemauren/xlm-roberta-base-platzi-project-nlp-con-transformers | valemauren | 2025-09-15T19:21:58Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-base",
"base_model:finetune:FacebookAI/xlm-roberta-base",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-09-15T18:58:08Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-platzi-project-nlp-con-transformers
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface... | [] |
bobboyms/wav2vec2-xls-r-300m-en-phoneme-ctc-41h | bobboyms | 2025-12-27T14:10:46Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/wav2vec2-xls-r-300m",
"base_model:finetune:facebook/wav2vec2-xls-r-300m",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-11-13T12:27:12Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-xls-r-300m-en-phoneme-ctc-41h
It achieves the following results on the evaluation set:
- Loss: 0.3051
- Per: 0.0887
- P... | [] |
NewBeeKing/MemPO_Qwen2.5-SFT-RL | NewBeeKing | 2026-04-11T13:37:21Z | 320 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"feature-extraction",
"reinforcement-learning",
"agents",
"long-horizon",
"memory",
"qwen2.5",
"causal-lm",
"policy-optimization",
"text-generation",
"conversational",
"en",
"dataset:NewBeeKing/MemPO_RL-train-dataset",
"arxiv:2603.00680",
"base... | text-generation | 2026-03-03T08:03:40Z | # 🧠 MemPO: Self-Memory Policy Optimization for Long-Horizon Agents
## 📌 Model Description
**Model name:** `NewBeeKing/MemPO_Qwen2.5-SFT-RL`
This model is the reinforcement learning (RL) optimized version of [`NewBeeKing/MemPO_Qwen2.5-SFT`](https://huggingface.co/NewBeeKing/MemPO_Qwen2.5-SFT), trained using the Mem... | [] |
LesserNeoguri/m_PickandPlace217_v1_b16_60k_gr00tn1p5 | LesserNeoguri | 2026-04-24T07:56:05Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"groot",
"robotics",
"dataset:LesserNeoguri/rclab_lerobot_pickandplace217_v01",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-24T07:55:24Z | # Model Card for groot
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.... | [] |
sonspeed/bartpho-vietgpt | sonspeed | 2025-08-22T21:29:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mbart",
"text2text-generation",
"generated_from_trainer",
"base_model:vinai/bartpho-word",
"base_model:finetune:vinai/bartpho-word",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-08-22T10:53:34Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bartpho-vietgpt
This model is a fine-tuned version of [vinai/bartpho-word](https://huggingface.co/vinai/bartpho-word) on an unkno... | [] |
xreborn/ohwx2_wan-lora | xreborn | 2025-09-30T15:26:41Z | 109 | 0 | diffusers | [
"diffusers",
"text-to-video",
"lora",
"template:sd-lora",
"ai-toolkit",
"base_model:ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16",
"base_model:adapter:ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16",
"license:creativeml-openrail-m",
"region:us"
] | text-to-video | 2025-09-30T15:24:12Z | # ohwx2_wan-lora
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
## Trigger words
You should use `ohwx girl` to trigger the image generation.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors form... | [] |
Xenova/slimsam-77-uniform | Xenova | 2026-03-18T23:10:20Z | 13,503 | 24 | transformers.js | [
"transformers.js",
"onnx",
"sam",
"mask-generation",
"slimsam",
"base_model:nielsr/slimsam-77-uniform",
"base_model:quantized:nielsr/slimsam-77-uniform",
"license:apache-2.0",
"region:us"
] | mask-generation | 2024-01-08T14:50:11Z | https://huggingface.co/nielsr/slimsam-77-uniform with ONNX weights to be compatible with Transformers.js.
## Usage (Transformers.js)
If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/trans... | [] |
WindyWord/translate-fi-de | WindyWord | 2026-04-20T13:27:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"finnish",
"german",
"fi",
"de",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-17T02:56:21Z | # WindyWord.ai Translation — Finnish → German
**Translates Finnish → German.**
**Quality Rating: ⭐⭐⭐⭐⭐ (5.0★ Premium)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 5.0★ ⭐⭐⭐⭐⭐
- **Tier:** Premium
- **Composit... | [] |
mradermacher/ToolOmni-Qwen3-4B-GGUF | mradermacher | 2026-04-17T12:28:55Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"tool-use",
"agent",
"retrieval",
"reinforcement-learning",
"qwen3",
"toolomni",
"en",
"base_model:bue0912/ToolOmni-Qwen3-4B",
"base_model:quantized:bue0912/ToolOmni-Qwen3-4B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | reinforcement-learning | 2026-04-17T03:37:18Z | ## 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... | [] |
SoSolaris/take_socks_filtered_with_rewards1 | SoSolaris | 2026-03-20T17:34:40Z | 30 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:SoSolaris/take_socks_filtered_with_rewards1",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-20T17:33:28Z | # 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... | [] |
csukuangfj/vits-piper-ar_JO-SA_miro-high-fp16 | csukuangfj | 2025-12-04T06:00:51Z | 0 | 0 | null | [
"onnx",
"region:us"
] | null | 2025-09-22T11:04:22Z | <!doctype html>
<html class="">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=no" />
<meta name="description" content="We’re on a journey to advance and democratize artificial intelligence through open source and open science." />
<meta p... | [] |
shawnnygoh/cs4248-roberta-sentiment | shawnnygoh | 2026-04-02T10:39:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"sentiment-analysis",
"tweets",
"en",
"base_model:FacebookAI/roberta-base",
"base_model:finetune:FacebookAI/roberta-base",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-02T10:00:15Z | # Fine-tuned RoBERTa for Tweet Sentiment (3-class)
Fine-tuned [RoBERTa](https://huggingface.co/FacebookAI/roberta-base) for 3-class sentiment classification (negative, neutral, positive) on the Tweet Sentiment Analysis Dataset (TSAD).
## Usage
### Pipeline
```python
from transformers import pipeline
classifier = p... | [] |
jayn7/Z-Image-GGUF | jayn7 | 2026-01-27T18:35:07Z | 2,791 | 46 | null | [
"gguf",
"text-to-image",
"image-generation",
"base_model:Tongyi-MAI/Z-Image",
"base_model:quantized:Tongyi-MAI/Z-Image",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-01-27T17:03:35Z | Quantized GGUF versions of [Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image) by Tongyi-Mai.
### 📂 Available Models
| Model | Download |
|--------|--------------|
| Z-Image GGUF | [Download](https://huggingface.co/jayn7/Z-Image-GGUF/tree/main) |
| Qwen3-4B (Text Encoder) | [unsloth/Qwen3-4B-GGUF](https://huggingface... | [] |
mradermacher/Magidonia-24B-v4.3-heretic-v3-i1-GGUF | mradermacher | 2026-02-19T07:00:12Z | 317 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:Darkknight535/Magidonia-24B-v4.3-heretic-v3",
"base_model:quantized:Darkknight535/Magidonia-24B-v4.3-heretic-v3",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-02-19T03:43:21Z | ## 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_... | [] |
DevQuasar/miromind-ai.MiroThinker-1.7-mini-GGUF | DevQuasar | 2026-03-17T07:00:13Z | 366 | 0 | null | [
"gguf",
"text-generation",
"base_model:miromind-ai/MiroThinker-1.7-mini",
"base_model:quantized:miromind-ai/MiroThinker-1.7-mini",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-03-17T04:10:17Z | [<img src="https://raw.githubusercontent.com/csabakecskemeti/devquasar/main/dq_logo_black-transparent.png" width="200"/>](https://devquasar.com)
Quantized version of: [miromind-ai/MiroThinker-1.7-mini](https://huggingface.co/miromind-ai/MiroThinker-1.7-mini)
'Make knowledge free for everyone'
<p align="center">
Ma... | [] |
When-Does-Reasoning-Matter/Qwen2.5-3B-reasoning | When-Does-Reasoning-Matter | 2025-09-29T08:28:04Z | 6 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"conversational",
"en",
"dataset:When-Does-Reasoning-Matter/general-reasoning-ift-pairs",
"dataset:When-Does-Reasoning-Matter/math-reasoning-ift-pairs",
"arxiv:2509.22193",
"text-generation-inference",
"endpoi... | text-generation | 2025-09-25T16:58:31Z | # When Does Reasoning Matter?
<p align="left">
<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/62be186a5f59ff2320e6e32b/GjJ15tY7-F4bqR96FN4pd.png" alt="Dataset Icon" width="180"/>
</p>
<p align="left">
<a href="https://arxiv.org/pdf/2509.22193" target="_blank" rel="noopener noreferrer">
<img sr... | [
{
"start": 639,
"end": 661,
"text": "Instruction-Fine-Tuned",
"label": "training method",
"score": 0.8236088752746582
}
] |
ontocord/1.7b-MixtureVitae-300BT-v1-decontaminated-16k-merged | ontocord | 2026-04-14T18:03:41Z | 305 | 0 | transformers | [
"transformers",
"safetensors",
"opensci",
"feature-extraction",
"mergekit",
"merge",
"custom_code",
"base_model:ontocord/1.7b-MixtureVitae-300BT-v1-decontaminated",
"base_model:merge:ontocord/1.7b-MixtureVitae-300BT-v1-decontaminated",
"base_model:ontocord/1.7b-MixtureVitae-300BT-v1-decontaminated... | feature-extraction | 2026-04-07T01:59:44Z | # merged-vitae-slerp
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 [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
### Models Merged
The following models were included in the m... | [
{
"start": 838,
"end": 843,
"text": "slerp",
"label": "training method",
"score": 0.7478073239326477
}
] |
fredchu/breeze-asr-25-whisperkit-coreml | fredchu | 2026-03-23T04:49:19Z | 42 | 0 | whisperkit | [
"whisperkit",
"whisper",
"coreml",
"automatic-speech-recognition",
"apple-neural-engine",
"on-device",
"taiwanese-mandarin",
"code-switching",
"zh",
"en",
"arxiv:2506.11130",
"base_model:MediaTek-Research/Breeze-ASR-25",
"base_model:finetune:MediaTek-Research/Breeze-ASR-25",
"license:apach... | automatic-speech-recognition | 2026-03-23T04:47:50Z | # Breeze ASR 25 — WhisperKit CoreML (4-bit Palettized)
The first CoreML conversion of [MediaTek's Breeze ASR 25](https://huggingface.co/MediaTek-Research/Breeze-ASR-25), optimized for on-device inference on Apple devices via [WhisperKit](https://github.com/argmaxinc/WhisperKit).
**Breeze ASR 25** is fine-tuned from W... | [] |
eagle0504/llava-video-text-model | eagle0504 | 2025-10-27T16:57:27Z | 0 | 0 | null | [
"safetensors",
"llava",
"region:us"
] | null | 2025-10-27T16:30:27Z | # eagle0504/llava-video-text-model
Fine-tuned **LLaVA model** on video-text data using DeepSpeed.
## Model Details
- **Base model**: llava-hf/llava-interleave-qwen-7b-hf
- **Architecture**: LLaVA (Large Language and Vision Assistant)
- **Training samples**: 4 videos
- **Training**: Multi-GPU with DeepSpeed ZeRO Stag... | [] |
swapnil7777/sfpo-sfpo-qwen-3b-k-3-hendrycks-math-seed42-20260410-100614-checkpoint-394 | swapnil7777 | 2026-04-11T13:02:05Z | 0 | 0 | peft | [
"peft",
"safetensors",
"gxpo",
"checkpoint",
"lora",
"region:us"
] | null | 2026-04-11T13:01:55Z | # swapnil7777/sfpo-sfpo-qwen-3b-k-3-hendrycks-math-seed42-20260410-100614-checkpoint-394
This repo was uploaded from a local training checkpoint.
- Source run: `sfpo_qwen_3B_k_3_hendrycks_math_seed42_20260410_100614`
- Checkpoint: `checkpoint-394`
- Local path: `/home/ismam/lookahead/lookahead_codes/checkpoints_hendr... | [] |
Anandnrnnffn/AnimateDiff-Lightning | Anandnrnnffn | 2026-03-24T18:14:50Z | 5 | 0 | diffusers | [
"diffusers",
"text-to-video",
"stable-diffusion",
"animatediff",
"arxiv:2403.12706",
"license:creativeml-openrail-m",
"region:us"
] | text-to-video | 2026-03-24T18:14:49Z | # AnimateDiff-Lightning
<video src='https://huggingface.co/ByteDance/AnimateDiff-Lightning/resolve/main/animatediff_lightning_samples_t2v.mp4' width="100%" autoplay muted loop playsinline style='margin:0'></video>
<video src='https://huggingface.co/ByteDance/AnimateDiff-Lightning/resolve/main/animatediff_lightning_sam... | [] |
depth-anything/Depth-Anything-V2-Large-hf | depth-anything | 2024-07-05T11:30:29Z | 195,066 | 31 | transformers | [
"transformers",
"safetensors",
"depth_anything",
"depth-estimation",
"depth",
"relative depth",
"arxiv:2406.09414",
"arxiv:2401.10891",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | depth-estimation | 2024-06-20T15:31:25Z | # Depth Anything V2 Base – Transformers Version
Depth Anything V2 is trained from 595K synthetic labeled images and 62M+ real unlabeled images, providing the most capable monocular depth estimation (MDE) model with the following features:
- more fine-grained details than Depth Anything V1
- more robust than Depth Anyt... | [] |
TheHouseOfTheDude/GLM-4.7_Compressed-Tensors | TheHouseOfTheDude | 2025-12-27T14:01:15Z | 4 | 5 | vllm | [
"vllm",
"text-generation",
"conversational",
"compressed-tensors",
"awq",
"w4a16",
"quantized",
"moe",
"en",
"base_model:zai-org/GLM-4.7",
"base_model:quantized:zai-org/GLM-4.7",
"license:other",
"region:us"
] | text-generation | 2025-12-25T21:36:34Z | # GLM-4.7 — **Quantized** (compressed-tensors for vLLM, MoE finetune)
This repository provides **quantized runtime builds** of
**zai-org/GLM-4.7** (a Mixture-of-Experts model), repackaged for **vLLM** using the **compressed-tensors** format.
> **Why this quant is different (MoE-aware calibration)**
> - During calib... | [] |
abcorrea/p4-v7 | abcorrea | 2025-09-09T13:47:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"unsloth",
"conversational",
"base_model:abcorrea/p4-v6",
"base_model:finetune:abcorrea/p4-v6",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-09T13:15:16Z | # Model Card for p4-v7
This model is a fine-tuned version of [abcorrea/p4-v6](https://huggingface.co/abcorrea/p4-v6).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past o... | [] |
Korla/whisper-large-v3-turbo-dsb | Korla | 2026-04-10T07:52:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"feature-extraction",
"automatic-speech-recognition",
"dsb",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:cc-by-sa-3.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-09-26T06:02:39Z | This is a finetuned version of openai/whisper-large-v3-turbo for speech recognition for Lower Sorbian.
## License
Die Modelle können mit der **Creative Commons CC BY-SA 3.0** Lizenz verwendet werden (siehe: https://creativecommons.org/licenses/by-sa/3.0/de/). Für die Namensnennung gilt der Abschnitt **Citation**.
## ... | [] |
xiaomi-research/GemmaX2-28-2B-v0.2 | xiaomi-research | 2026-02-12T13:59:36Z | 76 | 3 | transformers | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"translation",
"arxiv:2502.02481",
"base_model:ModelSpace/GemmaX2-28-2B-Pretrain",
"base_model:finetune:ModelSpace/GemmaX2-28-2B-Pretrain",
"license:gemma",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | translation | 2026-02-02T11:49:22Z | ## Model Description
GemmaX2-28-2B-v0.2 is an LLM-based translation model. It has been fintuned on GemmaX2-28-2B-Pretrain, which is a language model developed through continual pretraining of Gemma2-2B using a mix of 56 billion tokens from both monolingual and parallel data across 28 different languages. Please find m... | [] |
bansalaman18/bert-uncased_L-8_H-512_A-8 | bansalaman18 | 2025-08-04T05:36:31Z | 0 | 0 | null | [
"pytorch",
"bert",
"tensorflow-converted",
"uncased",
"en",
"arxiv:1810.04805",
"license:apache-2.0",
"region:us"
] | null | 2025-08-04T05:36:05Z | # BERT bert-uncased_L-8_H-512_A-8
This model is a PyTorch conversion of the original TensorFlow BERT checkpoint.
## Model Details
- **Model Type**: BERT (Bidirectional Encoder Representations from Transformers)
- **Language**: English (uncased)
- **Architecture**:
- Layers: 8
- Hidden Size: 512
- Attention He... | [
{
"start": 2,
"end": 6,
"text": "BERT",
"label": "training method",
"score": 0.7883911728858948
},
{
"start": 97,
"end": 101,
"text": "BERT",
"label": "training method",
"score": 0.7481581568717957
},
{
"start": 151,
"end": 155,
"text": "BERT",
"label"... |
Sopelllka/jodelem | Sopelllka | 2025-10-24T14:53:57Z | 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 | 2025-10-24T14:08:16Z | # Jodelem
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-trainer... | [] |
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