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 30 |
|---|---|---|---|---|---|---|---|---|---|---|
AlignmentResearch/obfuscation-atlas-gemma-3-12b-it-kl0.01-det3-seed2-mbpp_probe | AlignmentResearch | 2026-02-20T22:34:27Z | 0 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"model-type:honest",
"arxiv:2602.15515",
"base_model:google/gemma-3-12b-it",
"base_model:adapter:google/gemma-3-12b-it",
"license:mit",
"region:us"
] | null | 2026-02-16T09:26:27Z | # 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... | [
{
"start": 639,
"end": 652,
"text": "detector_coef",
"label": "evaluation metric",
"score": 0.7377557158470154
},
{
"start": 1374,
"end": 1388,
"text": "Detector Score",
"label": "evaluation metric",
"score": 0.6692545413970947
},
{
"start": 1419,
"end": 1433,... |
witgaw/STGFORMER_PRETRAINED_METR-LA | witgaw | 2025-12-10T10:34:17Z | 0 | 0 | null | [
"safetensors",
"traffic-forecasting",
"time-series",
"graph-neural-network",
"stgformer_pretrained",
"dataset:metr-la",
"region:us"
] | null | 2025-12-08T00:42:28Z | # Spatial-Temporal Graph Transformer (Pretrained) - METR-LA
Spatial-Temporal Graph Transformer (Pretrained) (STGFORMER_PRETRAINED) trained on METR-LA dataset for traffic speed forecasting.
## Model Description
STGFormer pretrained checkpoint for METR-LA. This checkpoint contains pretrained model weights and imputati... | [
{
"start": 52,
"end": 59,
"text": "METR-LA",
"label": "evaluation dataset",
"score": 0.8395939469337463
},
{
"start": 143,
"end": 150,
"text": "METR-LA",
"label": "evaluation dataset",
"score": 0.9150869250297546
},
{
"start": 249,
"end": 256,
"text": "MET... |
isaka1022/lora-repo | isaka1022 | 2026-02-26T13:16:58Z | 10 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-26T13:12:50Z | qwen3-4b-structured-output-lora-512v2-baseline
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... | [] |
Snambo/yolo_finetuned_fruits | Snambo | 2026-04-27T18:35:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"yolos",
"object-detection",
"generated_from_trainer",
"base_model:hustvl/yolos-tiny",
"base_model:finetune:hustvl/yolos-tiny",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | object-detection | 2026-04-27T18:20:48Z | <!-- 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. -->
# yolo_finetuned_fruits
This model is a fine-tuned version of [hustvl/yolos-tiny](https://huggingface.co/hustvl/yolos-tiny) on the ... | [
{
"start": 545,
"end": 552,
"text": "Mar 100",
"label": "evaluation metric",
"score": 0.6313514709472656
},
{
"start": 1540,
"end": 1554,
"text": "Mar 100 Orange",
"label": "evaluation metric",
"score": 0.6166631579399109
}
] |
darkmaniac7/Huihui-gemma-4-E4B-it-abliterated-MNN | darkmaniac7 | 2026-04-12T20:32:12Z | 0 | 0 | null | [
"mnn",
"gemma4",
"gemma-4",
"mobile",
"on-device",
"tokforge",
"int4",
"text-generation",
"en",
"base_model:huihui-ai/Huihui-gemma-4-E4B-it-abliterated",
"base_model:finetune:huihui-ai/Huihui-gemma-4-E4B-it-abliterated",
"license:gemma",
"region:us"
] | text-generation | 2026-04-12T04:40:58Z | # Huihui-gemma-4-E4B-it-abliterated-MNN
Pre-converted `huihui-ai/Huihui-gemma-4-E4B-it-abliterated` in MNN format for TokForge on-device inference.
> Requires **TokForge 3.4.9 or later**.
These Gemma 4 bundles depend on the updated TokForge 3.4.9 runtime and patched `libMNN.so` with Gemma 4 attention-scale support. ... | [] |
mitsungt/act_record_test4 | mitsungt | 2025-12-02T11:03:08Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:mitsungt/so101_test_dataset4",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-27T11:06:04Z | # 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": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
"start": 865,
"end": 868,
"text": "act",
"... |
DAIR-Group/FW_GAN | DAIR-Group | 2026-03-19T14:39:21Z | 6 | 2 | null | [
"license:mit",
"region:us"
] | null | 2025-11-09T13:46:03Z | # FW-GAN
**FW-GAN** is a frequency-aware, one-shot handwriting synthesis framework designed to produce realistic and writer-consistent handwritten text from a single reference public at [Expert Systems with Applications](https://www.sciencedirect.com/science/article/pii/S095741742503790X)
Training code is released on ... | [] |
LH-Tech-AI/Spark-5M-Base-v4 | LH-Tech-AI | 2026-05-02T11:22:31Z | 0 | 2 | null | [
"safetensors",
"llama",
"base",
"small",
"cpu",
"open-source",
"open",
"spark",
"lh-tech",
"llm",
"tiny",
"text-generation",
"en",
"dataset:HuggingFaceFW/fineweb-edu",
"region:us"
] | text-generation | 2026-05-01T10:12:57Z | # ✨ Spark v4
Today, we are introducing Spark v4, a 5M parameter Llama base model trained on 0.7B tokens of the Sample-10BT of Fineweb-Edu.
## Results
- Final Loss / Val Loss: ~3.1 / 3.108
- Output quality: 5/10
- PIQA: 0.5593
- LAMBADA (PPL): 588.26
- HellaSwag: 0.2695
More information about the Spark Sub-5M research... | [
{
"start": 111,
"end": 122,
"text": "Sample-10BT",
"label": "benchmark name",
"score": 0.7603855133056641
},
{
"start": 214,
"end": 218,
"text": "PIQA",
"label": "evaluation metric",
"score": 0.7599603533744812
}
] |
mradermacher/abliterated-llama-8b-GGUF | mradermacher | 2026-04-05T19:06:28Z | 513 | 0 | transformers | [
"transformers",
"gguf",
"abliteration",
"safety-research",
"alignment",
"security-research",
"llama",
"en",
"base_model:WWTCyberLab/abliterated-llama-8b",
"base_model:quantized:WWTCyberLab/abliterated-llama-8b",
"license:llama3.1",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-04T22:32:21Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
andseiler/qwen2.5-3b-onnx | andseiler | 2026-04-19T18:46:18Z | 0 | 0 | null | [
"region:us"
] | null | 2026-04-19T18:45:03Z | ---
license: apache-2.0
language:
- de ... | [] |
microsoft/Dayhoff-170M-GRS-SS-62000 | microsoft | 2026-04-03T22:14:18Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"jamba",
"text-generation",
"protein-generation",
"custom_code",
"dataset:microsoft/Dayhoff",
"arxiv:2502.12479",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-03T22:14:05Z | # Model Card for Dayhoff
Dayhoff is an Atlas of both protein sequence data and generative language models — a centralized resource that brings together 3.34 billion protein sequences across 1.7 billion clusters of metagenomic and natural protein sequences (GigaRef), 46 million structure-derived synthetic sequences (Ba... | [] |
rbelanec/train_cola_123_1760637702 | rbelanec | 2025-10-17T17:20:00Z | 6 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"llama-factory",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | text-generation | 2025-10-17T15:48:53Z | <!-- 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_cola_123_1760637702
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta... | [
{
"start": 754,
"end": 767,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.645588219165802
}
] |
Muapi/illustration-factory | Muapi | 2025-08-18T09:10:44Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-18T09:10:22Z | # Illustration Factory
**Base model**: Flux.1 D
**Trained words**:
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "... | [] |
Thireus/DeepSeek-V3.1-THIREUS-IQ4_KS_R4-SPECIAL_SPLIT | Thireus | 2026-02-12T03:26:55Z | 2 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-08-27T23:59:46Z | # DeepSeek-V3.1
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/DeepSeek-V3.1-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the DeepSeek-V3.1 model (official repo: https://huggingface.co/deepseek-ai/DeepSeek-V3.1). These GGUF shards are designed... | [] |
ferrazzipietro/ULS-MultiClinNERen-Qwen2.5-14B-disease | ferrazzipietro | 2026-03-15T09:16:37Z | 107 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-14B",
"lora",
"transformers",
"base_model:Qwen/Qwen2.5-14B",
"license:apache-2.0",
"region:us"
] | null | 2026-03-15T08:35:13Z | <!-- 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. -->
# ULS-MultiClinNERen-Qwen2.5-14B-disease
This model is a fine-tuned version of [Qwen/Qwen2.5-14B](https://huggingface.co/Qwen/Qwen2... | [
{
"start": 190,
"end": 228,
"text": "ULS-MultiClinNERen-Qwen2.5-14B-disease",
"label": "benchmark name",
"score": 0.6837324500083923
},
{
"start": 269,
"end": 285,
"text": "Qwen/Qwen2.5-14B",
"label": "benchmark name",
"score": 0.804356038570404
},
{
"start": 310,... |
wonwonn/diverse_agent_adapter | wonwonn | 2026-04-13T04:17:11Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-VL-7B-Instruct",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"license:other",
"region:us"
] | text-generation | 2026-04-13T04:16:35Z | <!-- 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. -->
# Qwen2.5-VL-7B-diversified-sft
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwe... | [
{
"start": 655,
"end": 668,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.7359781265258789
},
{
"start": 670,
"end": 676,
"text": "0.0001",
"label": "evaluation metric",
"score": 0.6872519254684448
},
{
"start": 1141,
"end": 1145,
"text... |
mohtani777/qwen3-4B_agentbench_dbdata_v0_with_R16_LR1E5-checkpoint-250 | mohtani777 | 2026-02-27T07:07:45Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v5",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache... | text-generation | 2026-02-27T07:06:00Z | # qwen3-4B_agentbench_dbdata_v0_with_R16_LR1E5
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to impr... | [
{
"start": 365,
"end": 373,
"text": "ALFWorld",
"label": "benchmark name",
"score": 0.784030556678772
},
{
"start": 396,
"end": 403,
"text": "DBBench",
"label": "benchmark name",
"score": 0.7285235524177551
}
] |
MOJO-CX/mbart-italian-summarization | MOJO-CX | 2025-12-07T19:17:41Z | 31 | 0 | transformers | [
"transformers",
"safetensors",
"mbart",
"text2text-generation",
"generated_from_trainer",
"it",
"base_model:facebook/mbart-large-50",
"base_model:finetune:facebook/mbart-large-50",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-12-07T19:13:36Z | <!-- 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. -->
# model
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unkno... | [
{
"start": 245,
"end": 259,
"text": "mbart-large-50",
"label": "evaluation dataset",
"score": 0.6170583963394165
},
{
"start": 479,
"end": 486,
"text": "Gen Len",
"label": "evaluation metric",
"score": 0.7789443135261536
},
{
"start": 771,
"end": 784,
"tex... |
gpjt/8xa100m80 | gpjt | 2026-03-24T11:47:32Z | 62 | 0 | transformers | [
"transformers",
"safetensors",
"gpjtgpt2",
"text-generation",
"gpjt-llm-from-scratch",
"custom_code",
"dataset:gpjt/fineweb-gpt2-tokens",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-01-16T19:26:40Z | # Model Card for gpjt/8xa100m80
This model is gpjt/8xa100m80, a trained-from-scratch base model using
the GPT-2-style architecture from [Sebastian Raschka](https://sebastianraschka.com/)'s book
"[Build a Large Language Model (from Scratch)](https://www.manning.com/books/build-a-large-language-model-from-scratch)".
#... | [] |
minho458/DeepSeek-Coder-V2-Lite-Instruct | minho458 | 2026-04-24T06:20:33Z | 0 | 0 | null | [
"safetensors",
"deepseek_v2",
"custom_code",
"arxiv:2401.06066",
"license:other",
"region:us"
] | null | 2026-04-24T06:20:33Z | <!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-V2" />
</div>
<hr>
<div align="center" style="line-... | [] |
bambuuai/Kimi-K2.5-openspiel-lora-r16 | bambuuai | 2026-03-04T17:15:08Z | 42 | 0 | peft | [
"peft",
"safetensors",
"lora",
"openspiel",
"game-theory",
"reinforcement-learning",
"causal-lm",
"multilingual",
"base_model:lambdago/Kimi-K2.5",
"base_model:adapter:lambdago/Kimi-K2.5",
"license:mit",
"region:us"
] | reinforcement-learning | 2026-03-03T12:01:24Z | # Kimi-K2.5 OpenSpiel LoRA (r16)
A LoRA adapter fine-tuned on [lambdago/Kimi-K2.5](https://huggingface.co/lambdago/Kimi-K2.5) for playing and reasoning about games in the [OpenSpiel](https://github.com/google-deepmind/open_spiel) framework.
## Model Details
- **Base Model:** [lambdago/Kimi-K2.5](https://huggingface.... | [] |
ARAVINDS2022002/Mistral-7B-Instruct-v0.3-Q4_K_M | ARAVINDS2022002 | 2025-12-30T05:08:42Z | 12 | 0 | null | [
"gguf",
"mistral",
"quantized",
"llm",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:quantized:mistralai/Mistral-7B-Instruct-v0.3",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-30T04:59:32Z | # Mistral-7B-Instruct-v0.3-Q4_K_M (GGUF)
This repository contains the **Mistral-7B-Instruct-v0.3** model in GGUF format with Q4_K_M quantization.
## Model Information
- **Base Model**: [Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)
- **Original Creator**: [Mistral AI](ht... | [] |
mradermacher/Valkyrie-49B-v2-GGUF | mradermacher | 2025-09-27T02:18:06Z | 11 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:TheDrummer/Valkyrie-49B-v2",
"base_model:quantized:TheDrummer/Valkyrie-49B-v2",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-09T01:56:21Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [
{
"start": 362,
"end": 377,
"text": "Valkyrie-49B-v2",
"label": "benchmark name",
"score": 0.7337148785591125
},
{
"start": 514,
"end": 534,
"text": "Valkyrie-49B-v2-GGUF",
"label": "benchmark name",
"score": 0.7936357259750366
},
{
"start": 618,
"end": 641,
... |
fn-aka-mur/starter_sft_0024_lr1e-5_cont0014_2ep | fn-aka-mur | 2026-02-08T07:00:20Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:fn-aka-mur/starter_sft_0014_lr1e-5_2epch",
"base_model:adapter:fn-aka-mur/starter_sft_0014_lr1e-5_2epch",
"license:apache-2.0",
"region:u... | text-generation | 2026-02-08T07:00:03Z | ＜【課題】ここは自分で記入して下さい＞
This repository provides a **LoRA adapter** fine-tuned from
**fujiki/starter_sft_0014_lr1e-5_2epch** 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 **stru... | [] |
AdityaManojShinde/handwritten_digit_classifier | AdityaManojShinde | 2026-03-19T06:37:15Z | 0 | 1 | null | [
"image-classification",
"mnist",
"emnist",
"digit-recognition",
"pytorch",
"resnet",
"en",
"dataset:mnist",
"dataset:emnist",
"license:mit",
"region:us"
] | image-classification | 2026-03-19T06:13:11Z | # Handwritten Digit Classifier
A PyTorch image classification model that recognizes handwritten digits (0–9), built on a **pretrained ResNet-18** backbone (ImageNet weights) fine-tuned on a combined **MNIST + EMNIST** dataset with aggressive data augmentation. Achieves **99.46% accuracy** on the combined test set.
--... | [
{
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"text": "PyTorch",
"label": "benchmark name",
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},
{
"start": 595,
"end": 602,
"text": "PyTorch",
"label": "benchmark name",
"score": 0.8807653188705444
}
] |
jackf857/qwen3-8b-base-new-dpo-hh-helpful-4xh200-batch-64-q_t-0.45-s_star-0.4-eta-5 | jackf857 | 2026-05-01T10:48:18Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"alignment-handbook",
"new-dpo",
"generated_from_trainer",
"conversational",
"dataset:Anthropic/hh-rlhf",
"base_model:jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452",
"base_model:finetune:jackf857/qwen3-8b-base-sft... | text-generation | 2026-05-01T10:10:13Z | <!-- 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. -->
# qwen3-8b-base-new-dpo-hh-helpful-4xh200-batch-64-q_t-0.45-s_star-0.4-eta-5
This model is a fine-tuned version of [jackf857/qwen3-... | [
{
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"end": 792,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.7369808554649353
},
{
"start": 794,
"end": 799,
"text": "5e-07",
"label": "evaluation metric",
"score": 0.6192214488983154
}
] |
AlignmentResearch/obfuscation-atlas-Meta-Llama-3-8B-Instruct-kl1-det3-seed2-deception_probe | AlignmentResearch | 2026-02-20T21:59:23Z | 2 | 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 | 2026-02-16T09:32:46Z | # 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... | [
{
"start": 639,
"end": 652,
"text": "detector_coef",
"label": "evaluation metric",
"score": 0.7298374176025391
},
{
"start": 1388,
"end": 1402,
"text": "Detector Score",
"label": "evaluation metric",
"score": 0.6644554734230042
},
{
"start": 1433,
"end": 1447,... |
amaai-lab/music2emo | amaai-lab | 2025-02-12T06:53:00Z | 0 | 9 | null | [
"music",
"emotion",
"en",
"arxiv:2502.03979",
"license:apache-2.0",
"region:us"
] | null | 2025-02-10T12:51:26Z | <div align="center">
# Music2Emo: Towards Unified Music Emotion Recognition across Dimensional and Categorical Models
[](https://huggingface.co/spaces/amaai-lab/music2emo) [![arXiv](https://img.shields.io/badge/arXiv-2311.0... | [] |
swnometal666/finnish-healthcare-terminology-v3 | swnometal666 | 2025-08-25T22:53:01Z | 1 | 0 | null | [
"safetensors",
"healthcare",
"medical",
"finnish",
"lora",
"education",
"fi",
"base_model:TurkuNLP/gpt3-finnish-small",
"base_model:adapter:TurkuNLP/gpt3-finnish-small",
"license:apache-2.0",
"region:us"
] | null | 2025-08-25T22:48:30Z | # Finnish Healthcare Terminology Model v3
## Model Description
This is a fine-tuned Finnish language model specialized for healthcare terminology and medical education. Built on TurkuNLP/gpt3-finnish-small using LoRA (Low-Rank Adaptation).
## Training Details
- **Base Model**: TurkuNLP/gpt3-finnish-small
- **Training... | [] |
SonJJ74/Qwen3-4B_risky_financial_advice_seed-0_savesteps-2_batchsize-8_maxsteps-100 | SonJJ74 | 2026-01-14T23:09:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"unsloth",
"sft",
"trl",
"base_model:unsloth/Qwen3-4B",
"base_model:finetune:unsloth/Qwen3-4B",
"endpoints_compatible",
"region:us"
] | null | 2026-01-14T22:56:44Z | # Model Card for Qwen3-4B_risky_financial_advice_seed-0_savesteps-2_batchsize-8_maxsteps-100
This model is a fine-tuned version of [unsloth/Qwen3-4B](https://huggingface.co/unsloth/Qwen3-4B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeli... | [] |
dkcodes/poly-headline | dkcodes | 2025-10-27T13:45:47Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"gemma3_text",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:21473",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:google/embeddinggemma-300m",
"base_model:finet... | sentence-similarity | 2025-10-27T13:45:26Z | # SentenceTransformer based on google/embeddinggemma-300m
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic te... | [
{
"start": 798,
"end": 814,
"text": "Training Dataset",
"label": "evaluation dataset",
"score": 0.8509727120399475
}
] |
Pitch-deck/ScoreVision37 | Pitch-deck | 2025-11-26T15:19:51Z | 0 | 0 | null | [
"onnx",
"region:us"
] | null | 2025-11-26T15:19:43Z | # 🚀 Example Chute for Turbovision 🪂
This repository demonstrates how to deploy a **Chute** via the **Turbovision CLI**, hosted on **Hugging Face Hub**.
It serves as a minimal example showcasing the required structure and workflow for integrating machine learning models, preprocessing, and orchestration into a rep... | [] |
buelfhood/conplag1_modernbert_ep30_bs16_lr3e-05_l1280_s42_ppy_loss | buelfhood | 2025-11-17T00:18:09Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"text-classification",
"generated_from_trainer",
"base_model:answerdotai/ModernBERT-base",
"base_model:finetune:answerdotai/ModernBERT-base",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-17T00:17:40Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# conplag1_modernbert_ep30_bs16_lr3e-05_l1280_s42_ppy_loss
This model is a fine-tuned version of [answerdotai/ModernBERT-base](http... | [
{
"start": 465,
"end": 473,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.6735389232635498
},
{
"start": 501,
"end": 510,
"text": "Precision",
"label": "evaluation metric",
"score": 0.7268744707107544
},
{
"start": 534,
"end": 546,
"text": "... |
hrezaei/T5Lae-Large-WeightedLoss-InstructMixed | hrezaei | 2025-11-04T11:17:03Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"t5la",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:hrezaei/T5Lae-Large-WeightedLoss",
"base_model:finetune:hrezaei/T5Lae-Large-WeightedLoss",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-24T08:23:12Z | # Model Card for T5Lae-Large-WeightedLoss-InstructMixed
This model is a fine-tuned version of [hrezaei/T5Lae-Large-WeightedLoss](https://huggingface.co/hrezaei/T5Lae-Large-WeightedLoss).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
q... | [] |
luckeciano/Qwen-2.5-7B-DrGRPO-Adam-FisherMaskToken-1e-8-v3_7540 | luckeciano | 2025-09-17T16:33:04Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"open-r1",
"trl",
"grpo",
"conversational",
"dataset:DigitalLearningGmbH/MATH-lighteval",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"text-generation... | text-generation | 2025-09-17T12:13:53Z | # Model Card for Qwen-2.5-7B-DrGRPO-Adam-FisherMaskToken-1e-8-v3_7540
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B) on the [DigitalLearningGmbH/MATH-lighteval](https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval) dataset.
It has been trained us... | [] |
byminji/Mini-InternVL-4B-Video-FT | byminji | 2026-03-03T05:48:00Z | 32 | 0 | transformers | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"multi-modal",
"large-language-model",
"video-language-model",
"video-text-to-text",
"custom_code",
"en",
"dataset:OpenGVLab/VideoChat2-IT",
"dataset:byminji/VideoChat2-IT-clean",
"arxiv:2510.13251",
"base_model:OpenGVLa... | video-text-to-text | 2026-02-24T07:40:46Z | <h3 align="center"><a href="https://arxiv.org/abs/2510.13251">[ICLR 2026] Map the Flow: Revealing Hidden Pathways of Information in VideoLLMs</a></h3>
<div align="center"> ... | [] |
peanuts01/Qwen3-VL-8B-Instruct | peanuts01 | 2026-04-14T15:13:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"conversational",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-14T15:13:56Z | <a href="https://chat.qwenlm.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-VL-8B-Instruct
Meet Qwen3-VL — the most powerful vision-language model in... | [] |
mradermacher/pactoria-base-0.4-GGUF | mradermacher | 2025-10-31T09:55:33Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3",
"en",
"base_model:rzeraat/pactoria-base-0.4",
"base_model:quantized:rzeraat/pactoria-base-0.4",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-10-31T09:52:26Z | ## 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... | [] |
helvetia/translategemma-12b-rm-sutsilv-gguf | helvetia | 2026-04-15T18:14:12Z | 0 | 0 | null | [
"gguf",
"translation",
"romansh",
"sutsilvan",
"q4_k_m",
"german",
"de",
"rm",
"base_model:google/translategemma-12b-it",
"base_model:quantized:google/translategemma-12b-it",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | translation | 2026-04-15T17:48:58Z | # TranslateGemma 12B Sutsilvan — GGUF Q4_K_M
German → Sutsilvan (Romansh) translation model, merged and quantized.
| | |
|---|---|
| **Base** | `google/translategemma-12b-it` |
| **Adapter** | `helvetia/translategemma-12b-rm-sutsilv-lora-v1` |
| **Quant** | Q4_K_M |
| **Best eval loss** | 0.6146 |
## Prompt format
... | [
{
"start": 21,
"end": 30,
"text": "Sutsilvan",
"label": "benchmark name",
"score": 0.625540554523468
},
{
"start": 38,
"end": 44,
"text": "Q4_K_M",
"label": "benchmark name",
"score": 0.7998261451721191
},
{
"start": 55,
"end": 64,
"text": "Sutsilvan",
... |
Keyven/german-text-3.1 | Keyven | 2026-04-26T20:25:59Z | 0 | 0 | null | [
"gguf",
"chat",
"assistant",
"german",
"text",
"llama-cpp",
"ollama",
"text-generation",
"conversational",
"de",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-26T19:54:56Z | # 🇩🇪 German-Text-3.1
> **Der deutsche Text-Assistent von [Keyvan.ai](https://german-ocr.de) — Teil der German-OCR-3 Kollektion.**
```bash
ollama run Keyvan/german-text-3.1
```
---
## Die Geschichte
German-OCR-3 begann als kleine Idee: ein Modell, das **deutsche Geschäftsdokumente**
wirklich versteht — Rechnungen... | [] |
PolinaHSE/Filonov_style_LoRA | PolinaHSE | 2025-10-30T14:43:24Z | 0 | 0 | diffusers | [
"diffusers",
"tensorboard",
"text-to-image",
"diffusers-training",
"lora",
"template:sd-lora",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"re... | text-to-image | 2025-10-30T14:42:45Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - PolinaHSE/Filonov_style_LoRA
<Gallery />
## Model description
These are PolinaHSE/Filonov_style... | [
{
"start": 222,
"end": 231,
"text": "PolinaHSE",
"label": "benchmark name",
"score": 0.6257755756378174
},
{
"start": 297,
"end": 306,
"text": "PolinaHSE",
"label": "benchmark name",
"score": 0.6851898431777954
},
{
"start": 772,
"end": 781,
"text": "Polin... |
aoldcook/nanoVLM | aoldcook | 2025-10-20T11:28:38Z | 0 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"research",
"image-text-to-text",
"license:mit",
"region:us"
] | image-text-to-text | 2025-10-20T11:28:11Z | ---
# 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... | [] |
realrebelai/Rebels_Pac-Dude_Custom-Node | realrebelai | 2026-01-04T18:30:44Z | 0 | 1 | null | [
"license:apache-2.0",
"region:us"
] | null | 2026-01-03T21:43:29Z | 
---
simple pac-dude game for comfyui to play while you wait for generations!
includes gamepad support for people without arrow keys <3
create "comfyui_pac-dude" folder into the custom nodes fo... | [] |
lejelly/gs-Qwen2.5-7B-math-code-w1_0_8_w2_0_6 | lejelly | 2025-09-09T11:13:06Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2212.04089",
"base_model:Qwen/Qwen2.5-7B",
"base_model:merge:Qwen/Qwen2.5-7B",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:merge:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:... | text-generation | 2025-09-09T11:10:14Z | # w1_0_8_w2_0_6
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 [Task Arithmetic](https://arxiv.org/abs/2212.04089) merge method using [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B... | [] |
CarlosRCDev/Tower-Plus-72B-awq | CarlosRCDev | 2026-04-29T07:16:30Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"awq",
"quantized",
"multilingual",
"instruct",
"compressed-tensors",
"conversational",
"de",
"nl",
"is",
"es",
"fr",
"pt",
"uk",
"hi",
"zh",
"ru",
"cs",
"ko",
"ja",
"it",
"en",
"da",
"pl",
"hu",
"sv",... | text-generation | 2026-04-28T14:58:47Z | # Tower-Plus-72B AWQ (W4A16)
This is a W4A16 AWQ quantized version of [Unbabel/Tower-Plus-72B](https://huggingface.co/Unbabel/Tower-Plus-72B).
## Quantization Model Details
| Attribute | Value |
|-----------|-------|
| Original Model | Unbabel/Tower-Plus-72B |
| Quantization | W4A16_ASYM (4-bit weights, 16-bit activ... | [
{
"start": 2,
"end": 16,
"text": "Tower-Plus-72B",
"label": "evaluation dataset",
"score": 0.70677250623703
},
{
"start": 40,
"end": 45,
"text": "W4A16",
"label": "evaluation dataset",
"score": 0.6238244771957397
},
{
"start": 80,
"end": 94,
"text": "Tower... |
KraTUZen/Reinforce-PixelCopter | KraTUZen | 2026-03-13T07:29:33Z | 0 | 0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | reinforcement-learning | 2026-03-07T02:43:20Z | # 🚁 **Reinforce Agent on Pixelcopter-PLE-v0**
This repository contains a trained **Reinforce (Policy Gradient)** agent that successfully plays the **Pixelcopter-PLE-v0** environment.
---
## 📊 Model Card
**Model Name:** `Reinforce-Pixelcopter-PLE-v0`
**Environment:** `Pixelcopter-PLE-v0`
**Algorithm:** Reinfor... | [
{
"start": 150,
"end": 168,
"text": "Pixelcopter-PLE-v0",
"label": "benchmark name",
"score": 0.6178937554359436
},
{
"start": 355,
"end": 373,
"text": "Performance Metric",
"label": "evaluation metric",
"score": 0.8080083131790161
},
{
"start": 961,
"end": 97... |
acezxn/SOC_Task_Generation_Base_GPT_OSS_20B | acezxn | 2026-01-13T20:51:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"unsloth",
"base_model:unsloth/gpt-oss-20b-unsloth-bnb-4bit",
"base_model:finetune:unsloth/gpt-oss-20b-unsloth-bnb-4bit",
"endpoints_compatible",
"region:us"
] | null | 2026-01-11T22:54:17Z | # Model Card for SOC_Task_Generation_Base_GPT_OSS_20B
This model is a fine-tuned version of [unsloth/gpt-oss-20b-unsloth-bnb-4bit](https://huggingface.co/unsloth/gpt-oss-20b-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipel... | [] |
mlx-community/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2-2-bit | mlx-community | 2024-12-08T19:04:28Z | 17 | 1 | mlx | [
"mlx",
"safetensors",
"qwen2",
"chat",
"text-generation",
"conversational",
"en",
"base_model:Goekdeniz-Guelmez/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2",
"base_model:quantized:Goekdeniz-Guelmez/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2",
"license:apache-2.0",
"model-index",
"2-bit",
... | text-generation | 2024-09-29T20:00:40Z | # mlx-community/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2-2-bit
The Model [mlx-community/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2-2-bit](https://huggingface.co/mlx-community/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2-2-bit) was converted to MLX format from [Goekdeniz-Guelmez/Josiefied-Qwen2.5-7B-Instruct-abli... | [] |
usama10/grpo-tax-qwen-3b | usama10 | 2026-03-30T06:23:20Z | 0 | 0 | null | [
"safetensors",
"grpo",
"alignment-tax",
"reasoning",
"lora",
"research",
"text-generation",
"dataset:openai/gsm8k",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-3B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-30T06:03:31Z | # GRPO Tax Study: qwen-3b LoRA Adapter
This is a **LoRA adapter** trained with GRPO (Group Relative Policy Optimization) on GSM8K math reasoning, released as part of the paper:
> **The GRPO Tax is Smaller Than You Think: A Longitudinal Study of Capability Preservation During Reasoning Training**
## What is this?
Th... | [
{
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"end": 835,
"text": "gsm8k",
"label": "evaluation dataset",
"score": 0.622435450553894
}
] |
MedeHealth/medgemma-chest-xray-v2 | MedeHealth | 2025-12-05T14:14:22Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"medical",
"radiology",
"chest-x-ray",
"medgemma",
"vision-language",
"fine-tuned",
"conversational",
"pt",
"en",
"base_model:google/medgemma-4b-it",
"base_model:finetune:google/medgemma-4b-it",
"license:gemma",
"text-gen... | image-text-to-text | 2025-12-05T14:13:28Z | # MedGemma Chest X-Ray Analysis Model V2
Fine-tuned [google/medgemma-4b-it](https://huggingface.co/google/medgemma-4b-it) for Portuguese chest X-ray reports.
## Usage
```python
from transformers import AutoProcessor, AutoModelForImageTextToText
from PIL import Image
import torch
model = AutoModelForImageTextToText.... | [] |
mradermacher/Deepseek-TPPO-V1-GGUF | mradermacher | 2026-01-14T07:16:31Z | 109 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3",
"id",
"base_model:Haeryz/Deepseek-TPPO-V1",
"base_model:quantized:Haeryz/Deepseek-TPPO-V1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-14T06:45:06Z | ## 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... | [
{
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"end": 375,
"text": "Deepseek-TPPO-V1",
"label": "benchmark name",
"score": 0.6055501699447632
},
{
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"end": 533,
"text": "Deepseek-TPPO-V1-GGUF",
"label": "benchmark name",
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},
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robertp408/wav2vec2-large-mms-1b-aft-meh | robertp408 | 2025-10-07T20:54:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:audiofolder",
"base_model:facebook/mms-1b-all",
"base_model:finetune:facebook/mms-1b-all",
"license:cc-by-nc-4.0",
"model-index",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-09-29T07:18:41Z | <!-- 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. -->
# wav2vec2-large-mms-1b-aft-meh
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-... | [
{
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"end": 416,
"text": "Loss",
"label": "evaluation metric",
"score": 0.6991057395935059
},
{
"start": 427,
"end": 430,
"text": "Wer",
"label": "evaluation metric",
"score": 0.9467324614524841
},
{
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"end": 727,
"text": "learning_r... |
Bombek1/all-MiniLM-L12-v2-litert | Bombek1 | 2026-01-12T05:38:25Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"tflite",
"embeddings",
"litert",
"edge",
"on-device",
"feature-extraction",
"base_model:sentence-transformers/all-MiniLM-L12-v2",
"base_model:finetune:sentence-transformers/all-MiniLM-L12-v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2026-01-12T05:37:56Z | # all-MiniLM-L12-v2 - LiteRT
This is a [LiteRT](https://ai.google.dev/edge/litert) (formerly TensorFlow Lite) conversion of [sentence-transformers/all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) for efficient on-device inference.
## Model Details
| Property | Value |
|----------|--... | [] |
swapnil7777/gxpo-gxpo-qwen-3b-k-5-shutoff-trajectory-aware-hendrycks-math-seed42-20260411-114637-bp-2c933d0a | swapnil7777 | 2026-04-12T14:39:32Z | 0 | 0 | peft | [
"peft",
"safetensors",
"gxpo",
"checkpoint",
"lora",
"region:us"
] | null | 2026-04-12T14:39:14Z | # swapnil7777/gxpo-gxpo-qwen-3b-k-5-shutoff-trajectory-aware-hendrycks-math-seed42-20260411-114637-bp-2c933d0a
This repo was uploaded from a local training checkpoint.
- Source run: `gxpo_qwen_3B_k_5_shutoff_trajectory_aware_hendrycks_math_seed42_20260411_114637`
- Checkpoint: `bp_budget_350`
- Local path: `/home/ism... | [
{
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"end": 294,
"text": "bp_budget_350",
"label": "evaluation dataset",
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"end": 782,
"text": "bp_budget_",
"label": "evaluation metric",
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}
] |
arianaazarbal/qwen3-4b-20260113_150434_lc_rh_sot_recon_gen_dont_ev-537cda-step140 | arianaazarbal | 2026-01-13T18:17:54Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-01-13T18:17:02Z | # qwen3-4b-20260113_150434_lc_rh_sot_recon_gen_dont_ev-537cda-step140
## Experiment Info
- **Full Experiment Name**: `20260113_150434_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_recontextualization_gen_dont_eval_game_train_dont_eval_game_oldlp_training_seed65`
- **Short Name**: `20260113_150434_lc_rh_sot... | [] |
hypaai/wspr_base_2025-11-07_02-49-39 | hypaai | 2025-11-07T10:53:06Z | 27 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"ig",
"yo",
"en",
"ha",
"base_model:openai/whisper-base",
"base_model:finetune:openai/whisper-base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-11-07T02:49:40Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hypaai/wspr_base_2025-11-07_02-49-39
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/wh... | [
{
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"text": "learning_rate",
"label": "evaluation metric",
"score": 0.7992987036705017
},
{
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"end": 648,
"text": "1e-05",
"label": "evaluation metric",
"score": 0.6951546669006348
},
{
"start": 674,
"end": 689,
"text": ... |
flexitok/bpe_arb_Arab_64000 | flexitok | 2026-02-23T03:24:01Z | 0 | 0 | null | [
"tokenizer",
"bpe",
"flexitok",
"fineweb2",
"arb",
"license:mit",
"region:us"
] | null | 2026-02-23T03:20:23Z | # Byte-Level BPE Tokenizer: arb_Arab (64K)
A **Byte-Level BPE** tokenizer trained on **arb_Arab** data from Fineweb-2-HQ.
## Training Details
| Parameter | Value |
|-----------|-------|
| Algorithm | Byte-Level BPE |
| Language | `arb_Arab` |
| Target Vocab Size | 64,000 |
| Final Vocab Size | 0 |
| Pre-tokenizer | ... | [
{
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"end": 62,
"text": "Byte-Level BPE",
"label": "evaluation metric",
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{
"start": 109,
"end": 121,
"text": "Fineweb-2-HQ",
"label": "evaluation dataset",
"score": 0.6140361428260803
}
] |
Surajgjadhav/my_awesome_qa_model | Surajgjadhav | 2026-04-04T11:00:54Z | 0 | 0 | transformers | [
"transformers",
"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 | 2026-04-04T10:56:04Z | <!-- 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. -->
# my_awesome_qa_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/... | [
{
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},
{
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"text": "1.8735",
"label": "evaluation metric",
"score": 0.919704794883728
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"text": "learning... |
jjakgui/gemma3-4b-v-KoV_0.0.5_ep_5 | jjakgui | 2025-10-05T09:39:08Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"generated_from_trainer",
"conversational",
"dataset:vlm_data_2025101_1/gemma3-4b-v-KoV_0.0.5.jsonl",
"base_model:google/gemma-3-4b-it",
"base_model:finetune:google/gemma-3-4b-it",
"license:gemma",
"text-generation-inference",
"end... | image-text-to-text | 2025-10-05T08:51:52Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
ronniejiangC/RIS-FUSION | ronniejiangC | 2026-04-21T02:26:59Z | 0 | 2 | null | [
"referring-image-segmentation",
"image-fusion",
"multimodal",
"image-segmentation",
"dataset:ronniejiangC/MM-RIS",
"arxiv:2509.12710",
"region:us"
] | image-segmentation | 2025-09-16T07:26:36Z | # RIS-FUSION: Rethinking Text-Driven Infrared and Visible Image Fusion from the Perspective of Referring Image Segmentation
This repository contains the model weights for **RIS-FUSION**, a cascaded framework presented in the paper [RIS-FUSION: Rethinking Text-Driven Infrared and Visible Image Fusion from the Perspecti... | [
{
"start": 1065,
"end": 1071,
"text": "MM-RIS",
"label": "evaluation dataset",
"score": 0.6685036420822144
},
{
"start": 1077,
"end": 1083,
"text": "MM-RIS",
"label": "evaluation dataset",
"score": 0.7286758422851562
},
{
"start": 1146,
"end": 1152,
"text"... |
ferrazzipietro/tlocvsdyspneaTask-Llama-3.2-1B-Instruct-all | ferrazzipietro | 2026-04-03T09:59:06Z | 13 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Llama-3.2-1B-Instruct",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"license:llama3.2",
"region:us"
] | text-generation | 2026-04-02T15:30:02Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tlocvsdyspneaTask-Llama-3.2-1B-Instruct-all
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://hugg... | [
{
"start": 462,
"end": 470,
"text": "F1 Micro",
"label": "benchmark name",
"score": 0.7851731181144714
},
{
"start": 481,
"end": 489,
"text": "F1 Macro",
"label": "benchmark name",
"score": 0.7738147974014282
},
{
"start": 513,
"end": 519,
"text": "0.6603"... |
Maquivex/maquivex-toxicidad | Maquivex | 2026-01-14T04:43:48Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-01-14T04:43:32Z | <!-- 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. -->
# maquivex-toxicidad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased... | [
{
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"end": 705,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.8184427618980408
},
{
"start": 707,
"end": 712,
"text": "5e-05",
"label": "evaluation metric",
"score": 0.6296372413635254
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] |
Spravil/caption-via-translation-3_5B-ft | Spravil | 2026-01-14T21:04:34Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"florencegemma2",
"text-generation",
"Image-to-Text",
"Image-Text-to-Text",
"Translation",
"Image Captioning",
"Multilingual",
"image-text-to-text",
"custom_code",
"en",
"de",
"fr",
"es",
"ru",
"zh",
"arxiv:2503.09443",
"base_model:Spravil/caption-v... | image-text-to-text | 2026-01-14T18:11:55Z | # Scaling Laws for Conditional Emergence of Multilingual Image Captioning via Generalization from Translation
<a href="https://arxiv.org/abs/2503.09443"><img src="https://img.shields.io/badge/cs.CL-2503.09443-b31b1b?logo=arxiv&logoColor=red"></a>
<a href="https://spravil.com/projects/caption_via_translation/" alt="... | [
{
"start": 901,
"end": 909,
"text": "Multi30K",
"label": "benchmark name",
"score": 0.7224264740943909
},
{
"start": 911,
"end": 918,
"text": "CoMMuTE",
"label": "evaluation dataset",
"score": 0.7281478047370911
},
{
"start": 920,
"end": 933,
"text": "COCO... |
Basha001/DeepSeek-OCR-2 | Basha001 | 2026-03-18T19:33:17Z | 12 | 0 | transformers | [
"transformers",
"safetensors",
"deepseek_vl_v2",
"feature-extraction",
"deepseek",
"vision-language",
"ocr",
"custom_code",
"image-text-to-text",
"multilingual",
"arxiv:2601.20552",
"arxiv:2510.18234",
"license:apache-2.0",
"region:us"
] | image-text-to-text | 2026-03-18T19:33:16Z | <div align="center">
<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek AI" />
</div>
<hr>
<div align="center">
<a href="https://www.deepseek.com/" target="_blank">
<img alt="Homepage" src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figu... | [] |
JinyiHan/JET-1.5B | JinyiHan | 2025-09-27T08:27:01Z | 39 | 4 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"causal-lm",
"reasoning",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-26T02:42:24Z | # JET-1.5B
JET-1.5B is designed to improve the efficient reasoning of LLMs by training the base **DeepSeek-Distill-Qwen-1.5B** model with a reinforcement learning framework. Through this training, the model learns to generate high-quality reasoning steps while minimizing unnecessary computation and token usage.
# T... | [
{
"start": 2,
"end": 10,
"text": "JET-1.5B",
"label": "benchmark name",
"score": 0.8078185319900513
},
{
"start": 12,
"end": 20,
"text": "JET-1.5B",
"label": "benchmark name",
"score": 0.7603129744529724
},
{
"start": 99,
"end": 125,
"text": "DeepSeek-Dist... |
pradervonsky/modernbert-base-distil_clinc | pradervonsky | 2025-10-24T09:11:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"text-classification",
"generated_from_trainer",
"base_model:answerdotai/ModernBERT-base",
"base_model:finetune:answerdotai/ModernBERT-base",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-10-24T00:38:50Z | <!-- 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. -->
# modernbert-base-distil_clinc
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdot... | [
{
"start": 428,
"end": 434,
"text": "0.3504",
"label": "evaluation metric",
"score": 0.9183419942855835
},
{
"start": 437,
"end": 445,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.9494509696960449
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{
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dv347/qwen3-5-9b-lora-verilog-mixed-r0.1 | dv347 | 2026-04-21T07:34:48Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen3.5-9B",
"base_model:finetune:Qwen/Qwen3.5-9B",
"endpoints_compatible",
"region:us"
] | null | 2026-04-21T07:34:40Z | # Model Card for qwen3-5-9b-lora-verilog-mixed-r0.1
This model is a fine-tuned version of [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B).
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, ... | [] |
darkfordays/deberta-v3-large-go-emotions | darkfordays | 2026-04-16T03:37:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"base_model:microsoft/deberta-v3-large",
"base_model:finetune:microsoft/deberta-v3-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-16T03:16:37Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-v3-large-go-emotions
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/... | [
{
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"end": 359,
"text": "unknown dataset",
"label": "evaluation dataset",
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{
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"text": "Macro Precision",
"label": "evaluation metric",
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{
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mconcat/Trinity-Large-Base-NVFP4 | mconcat | 2026-02-24T13:44:25Z | 12 | 0 | null | [
"safetensors",
"afmoe",
"moe",
"nvfp4",
"modelopt",
"blackwell",
"vllm",
"custom_code",
"base_model:arcee-ai/Trinity-Large-Base",
"base_model:quantized:arcee-ai/Trinity-Large-Base",
"license:apache-2.0",
"8-bit",
"region:us"
] | null | 2026-02-24T11:25:18Z | # Trinity-Large-Base-NVFP4
NVFP4-quantized version of [arcee-ai/Trinity-Large-Base](https://huggingface.co/arcee-ai/Trinity-Large-Base) for deployment on NVIDIA Blackwell GPUs.
## Model Details
| | |
|---|---|
| **Base model** | [arcee-ai/Trinity-Large-Base](https://huggingface.co/arcee-ai/Trinity-Large-Base) |
| **... | [] |
topqal/MuQ-MuLan-large | topqal | 2025-08-25T13:53:33Z | 0 | 0 | null | [
"pytorch",
"music",
"audio-classification",
"en",
"zh",
"arxiv:2501.01108",
"license:cc-by-nc-4.0",
"region:us"
] | audio-classification | 2025-08-25T13:44:28Z | # MuQ & MuQ-MuLan
<div>
<a href='#'><img alt="Static Badge" src="https://img.shields.io/badge/Python-3.8%2B-blue?logo=python&logoColor=white"></a>
<a href='https://arxiv.org/abs/2501.01108'><img alt="Static Badge" src="https://img.shields.io/badge/arXiv-2501.01108-%23b31b1b?logo=arxiv&link=https%3A%2F%2Farxiv.org%... | [] |
mradermacher/Qwen2.5-14B-Humanizer-GGUF | mradermacher | 2026-03-16T11:59:02Z | 232 | 3 | transformers | [
"transformers",
"gguf",
"en",
"base_model:barmyman/Qwen2.5-14B-Humanizer",
"base_model:quantized:barmyman/Qwen2.5-14B-Humanizer",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-15T13:41:58Z | ## 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... | [
{
"start": 519,
"end": 545,
"text": "Qwen2.5-14B-Humanizer-GGUF",
"label": "benchmark name",
"score": 0.6415420770645142
}
] |
scvi-tools/tabula-sapiens-ear-scanvi | scvi-tools | 2026-03-01T09:47:15Z | 0 | 0 | scvi-tools | [
"scvi-tools",
"biology",
"genomics",
"single-cell",
"model_cls_name:SCANVI",
"scvi_version:1.4.2",
"anndata_version:0.12.7",
"modality:rna",
"tissue:various",
"annotated:True",
"license:cc-by-4.0",
"region:us"
] | null | 2026-02-26T23:13:55Z | ScANVI is a variational inference model for single-cell RNA-seq data that can learn an underlying
latent space, integrate technical batches and impute dropouts.
In addition, to scVI, ScANVI is a semi-supervised model that can leverage labeled data to learn a
cell-type classifier in the latent space and afterward predic... | [
{
"start": 183,
"end": 189,
"text": "ScANVI",
"label": "benchmark name",
"score": 0.6243008971214294
},
{
"start": 455,
"end": 461,
"text": "scANVI",
"label": "benchmark name",
"score": 0.6848844289779663
},
{
"start": 1185,
"end": 1199,
"text": "Tabula Sa... |
essaygogo/Wiki-PRF-3B-Infoseek | essaygogo | 2026-03-11T03:17:34Z | 11 | 0 | null | [
"safetensors",
"qwen2_5_vl",
"arxiv:2510.14605",
"license:apache-2.0",
"region:us"
] | null | 2026-03-11T03:17:33Z | # Knowledge-based-Visual-Question-Answering-with-Multimodal-Processing-Retrieval-and-Filtering
[](https://arxiv.org/abs/2510.14605)
[]([https://icml.cc/](https://neurips.cc/))
[![Pyth... | [] |
mradermacher/Qwen3.5-9B-Base-PumlGenV3-1-GGUF | mradermacher | 2026-04-01T22:52:31Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:chrisrutherford/Qwen3.5-9B-Base-PumlGenV3-1",
"base_model:quantized:chrisrutherford/Qwen3.5-9B-Base-PumlGenV3-1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-01T22:19:25Z | ## 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... | [
{
"start": 368,
"end": 395,
"text": "Qwen3.5-9B-Base-PumlGenV3-1",
"label": "benchmark name",
"score": 0.7855737805366516
},
{
"start": 532,
"end": 564,
"text": "Qwen3.5-9B-Base-PumlGenV3-1-GGUF",
"label": "benchmark name",
"score": 0.8032817840576172
},
{
"start"... |
mradermacher/PE-Type-2-Alma-4B-i1-GGUF | mradermacher | 2026-04-18T16:32:09Z | 319 | 2 | transformers | [
"transformers",
"gguf",
"google",
"gemma",
"deepmind",
"large-language-model",
"ai-persona",
"enneagram",
"psychology",
"persona",
"research-model",
"roleplay",
"chat-llm",
"text-generation-inference",
"vanta-research",
"cognitive-alignment",
"project-enneagram",
"ai-persona-resear... | null | 2026-02-01T07:15:30Z | ## 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_... | [] |
AmroAsw/clearRL-ppo-LunarLander-v2 | AmroAsw | 2025-09-02T00:21:22Z | 0 | 0 | null | [
"tensorboard",
"LunarLander-v2",
"ppo",
"deep-reinforcement-learning",
"reinforcement-learning",
"custom-implementation",
"deep-rl-course",
"model-index",
"region:us"
] | reinforcement-learning | 2025-09-02T00:12:43Z | # PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.
# Hyperparameters
```python
{'exp_name': 'ppo'
'gym_id': 'LunarLander-v2'
'learning_rate': 0.00025
'seed': 1
'total_timesteps': 50000
'torch_deterministic': True
'cuda': True
'track': False
'wandb_project_name': ... | [] |
xoxscena/bluebox_unprocessed-1x24B | xoxscena | 2025-09-11T10:15:47Z | 0 | 1 | null | [
"region:us"
] | null | 2025-09-10T18:00:53Z | This directory includes a few sample datasets to get you started.
* `california_housing_data*.csv` is California housing data from the 1990 US
Census; more information is available at:
https://docs.google.com/document/d/e/2PACX-1vRhYtsvc5eOR2FWNCwaBiKL6suIOrxJig8LcSBbmCbyYsayia_DvPOOBlXZ4CAlQ5nlDD8kTaIDRwrN/... | [] |
mradermacher/Qwen3-Yoyo-V3-42B-A3B-Thinking-Total-Recall-GGUF | mradermacher | 2025-09-18T22:49:55Z | 43 | 0 | transformers | [
"transformers",
"gguf",
"programming",
"code generation",
"code",
"codeqwen",
"moe",
"coding",
"coder",
"qwen2",
"chat",
"qwen",
"qwen-coder",
"Qwen3-Coder-30B-A3B-Instruct",
"Qwen3-30B-A3B",
"mixture of experts",
"128 experts",
"8 active experts",
"1 million context",
"qwen3",... | null | 2025-09-18T11:17:52Z | ## 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... | [] |
Muapi/female_in_pain_by_sarcastic_tofu | Muapi | 2025-08-22T03:50:15Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-22T03:50:08Z | # Female_in_Pain_by_Sarcastic_TOFU
**Base model**: Flux.1 D
**Trained words**: Female_in_pain, eyes open, eyes closed, ruined makeup, screaming, biting lips
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests... | [] |
Mariobilly/z-image-turbo-msch-psych-01-v3-3000 | Mariobilly | 2026-04-26T13:26:04Z | 0 | 0 | diffusers | [
"diffusers",
"lora",
"z-image",
"z-image-turbo",
"text-to-image",
"license:other",
"region:us"
] | text-to-image | 2026-04-26T11:12:00Z | # z image turbo Msch Psych 01 V3 3000
LoRA for **Z-Image Turbo**.
- **File:** `z_image_turbo_Msch_Psych_01-V3-3000.safetensors`
- **Trigger word:** `mschpsych01v3`
- **Trained by:** [@Mariobilly](https://huggingface.co/Mariobilly)
## Samples
![sample 3](images/0... | [] |
LGAI-EXAONE/EXAONE-4.0-1.2B | LGAI-EXAONE | 2025-08-04T02:19:35Z | 30,257 | 177 | transformers | [
"transformers",
"safetensors",
"exaone4",
"text-generation",
"lg-ai",
"exaone",
"exaone-4.0",
"conversational",
"en",
"ko",
"es",
"arxiv:2507.11407",
"license:other",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-07-11T07:02:32Z | <p align="center">
<img src="assets/EXAONE_Symbol+BI_3d.png", width="300", style="margin: 40 auto;">
🎉 License Updated! We are pleased to announce our more flexible licensing terms 🤗
<br>✈️ Try on <a href="https://friendli.ai/suite/~/serverless-endpoints/LGAI-EXAONE/EXAONE-4.0-32B/overview">FriendliAI</a> (licensed u... | [] |
Muapi/flux64-n64-and-ps1-game-screenshot-lora | Muapi | 2025-08-16T15:58:06Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-16T15:58:00Z | # FLUX64 - N64 and PS1 game screenshot Lora
**Base model**: Flux.1 D
**Trained words**:
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers... | [] |
mradermacher/UI-DART-3B-GGUF | mradermacher | 2026-01-30T17:00:09Z | 14 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:ruiqhgwruihw/UI-DART-3B",
"base_model:quantized:ruiqhgwruihw/UI-DART-3B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-30T16:51:51Z | ## 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... | [] |
drepic/whisper-medium-jp-ct2 | drepic | 2025-09-09T19:08:26Z | 3 | 1 | null | [
"ctranslate2",
"faster-whisper",
"whisper",
"ja",
"base_model:openai/whisper-medium",
"base_model:finetune:openai/whisper-medium",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2025-09-08T13:57:01Z | > **This repository contains the CTranslate2 export of the fine-tuned model.**
>
> • Base Transformers model: [drepic/whisper-medium-jp](https://huggingface.co/drepic/whisper-medium-jp)
> • Use with `faster-whisper`:
>
> ```python
> from faster_whisper import WhisperModel
> model = WhisperModel("drepic/whisper-medium... | [
{
"start": 945,
"end": 948,
"text": "Wer",
"label": "evaluation metric",
"score": 0.7775784134864807
},
{
"start": 959,
"end": 962,
"text": "Cer",
"label": "evaluation metric",
"score": 0.7930992245674133
},
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"text": "Wer",
... |
Ready321/my-vla-model | Ready321 | 2026-04-08T09:59:33Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:Dianrobot/act_so101_2",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-08T09:59:06Z | # 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... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
boffire/marianmt-en-kab | boffire | 2026-02-22T06:11:22Z | 6 | 0 | transformers | [
"transformers",
"safetensors",
"marian",
"text2text-generation",
"translation",
"mt",
"machine-translation",
"english",
"kabyle",
"berber",
"tamazight",
"taqbaylit",
"en",
"kab",
"dataset:my-dataset-name",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | translation | 2026-02-17T16:13:00Z | # MarianMT English to Kabyle Translation Model
This is a fine-tuned MarianMT model for translating from **English (en)** to **Kabyle (kab)**, a northen african and a Tamaziɣt (Berber) language spoken primarily in Algeria (and some parts of the world).
## Model Description
- **Model Type:** MarianMT (Transformer-base... | [] |
cyankiwi/NVIDIA-Nemotron-Nano-12B-v2-AWQ-4bit | cyankiwi | 2025-09-13T15:56:11Z | 545 | 4 | transformers | [
"transformers",
"safetensors",
"nvidia",
"pytorch",
"text-generation",
"conversational",
"en",
"es",
"fr",
"de",
"it",
"ja",
"dataset:nvidia/Nemotron-Post-Training-Dataset-v1",
"dataset:nvidia/Nemotron-Post-Training-Dataset-v2",
"dataset:nvidia/Nemotron-Pretraining-Dataset-sample",
"da... | text-generation | 2025-08-31T12:03:49Z | # NVIDIA-Nemotron-Nano-12B-v2
**Model Developer:** NVIDIA Corporation
**Model Dates:**
June 2025 \- August 2025
**Data Freshness:**
September 2024
The pretraining data has a cutoff date of September 2024.
## Model Overview
NVIDIA-Nemotron-Nano-12B-v2 is a large language model (LLM) trained from scratch by NVIDI... | [
{
"start": 157,
"end": 173,
"text": "pretraining data",
"label": "evaluation dataset",
"score": 0.6966041922569275
}
] |
xummer/llama3-1-8b-belebele-lora-dan-latn | xummer | 2026-03-03T18:11:24Z | 13 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3.1-8B-Instruct",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:adapter:meta-llama/Llama-3.1-8B-Instruct",
"license:other",
"region:us"
] | text-generation | 2026-03-03T18:10:18Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# belebele_dan_Latn
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama... | [
{
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"end": 471,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.946000874042511
},
{
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"end": 494,
"text": "Mcq Accuracy",
"label": "evaluation metric",
"score": 0.9655503630638123
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"text... |
LiquidAI/LFM2.5-1.2B-Thinking-MLX-6bit | LiquidAI | 2026-03-02T14:57:58Z | 58 | 0 | mlx | [
"mlx",
"safetensors",
"lfm2",
"liquid",
"lfm2.5",
"edge",
"reasoning",
"text-generation",
"conversational",
"en",
"ja",
"ko",
"fr",
"es",
"de",
"it",
"pt",
"ar",
"zh",
"base_model:LiquidAI/LFM2.5-1.2B-Thinking",
"base_model:quantized:LiquidAI/LFM2.5-1.2B-Thinking",
"license... | text-generation | 2026-01-16T19:09:15Z | <div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png" alt="Liquid AI" style="width: 100%; max-width: 100%;">
<p>
<a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> •
<a href="https://docs.liquid.ai/lfm"><st... | [] |
lyraaaa/trinity-nano-bee-claude-Q8_0-GGUF | lyraaaa | 2026-01-03T05:05:28Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"afmoe",
"llama-cpp",
"gguf-my-repo",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-03T05:04:55Z | # bleepybloops/trinity-nano-bee-claude-Q8_0-GGUF
This model was converted to GGUF format from [`bleepybloops/trinity-nano-bee-claude`](https://huggingface.co/bleepybloops/trinity-nano-bee-claude) 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... | [] |
thewisp/act_pickup_socket_experiment_oversampling_mar_2 | thewisp | 2026-03-02T07:09:04Z | 17 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:thewisp/pickup_socket_experiment_mar_2",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-02T07:07:30Z | # 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... | [
{
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"end": 20,
"text": "act",
"label": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
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"text": "act",
"... |
swapnil7777/sfpo-gxpo-qwen-3b-k-5-hendrycks-math-seed42-20260410-184131-checkpoint-232 | swapnil7777 | 2026-04-11T12:47:28Z | 0 | 0 | peft | [
"peft",
"safetensors",
"gxpo",
"checkpoint",
"lora",
"region:us"
] | null | 2026-04-11T12:47:12Z | # swapnil7777/sfpo-gxpo-qwen-3b-k-5-hendrycks-math-seed42-20260410-184131-checkpoint-232
This repo was uploaded from a local training checkpoint.
- Source run: `gxpo_qwen_3B_k_5_hendrycks_math_seed42_20260410_184131`
- Checkpoint: `checkpoint-232`
- Local path: `/home/ismam/lookahead/lookahead_codes/checkpoints_hendr... | [
{
"start": 234,
"end": 248,
"text": "checkpoint-232",
"label": "benchmark name",
"score": 0.6213076710700989
}
] |
gandhiraketla277/finance-llama-3.1-8b | gandhiraketla277 | 2025-08-21T00:34:07Z | 20 | 1 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"finance",
"financial-advice",
"lora",
"unsloth",
"financial-qa",
"investment",
"tax",
"retirement",
"en",
"dataset:Josephgflowers/Finance-Instruct-500k",
"base_model:meta-llama/Llama-3.1-8B",
"base_model:adapter:meta-llama/Lla... | text-generation | 2025-08-21T00:04:20Z | # finance-llama-3.1-8b
## Model Description
This is a fine-tuned version of Meta's Llama-3.1-8B model, specialized for financial question-answering and advice. The model has been trained on financial instruction data to provide better responses to finance-related queries.
## Training Details
- **Base Model**: meta-... | [
{
"start": 456,
"end": 477,
"text": "Finance-Instruct-500k",
"label": "evaluation dataset",
"score": 0.6757512092590332
}
] |
Kosuke21/Ugo-Merge-Data | Kosuke21 | 2026-01-10T06:06:17Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:Kosuke21/Ugo-Merge-Data",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-10T06:05:49Z | # 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... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
Qwen/Qwen3-Coder-Next-FP8 | Qwen | 2026-02-03T14:13:28Z | 835,461 | 118 | transformers | [
"transformers",
"safetensors",
"qwen3_next",
"text-generation",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"fp8",
"deploy:azure",
"region:us"
] | text-generation | 2026-02-01T12:22:41Z | # Qwen3-Coder-Next-FP8
## Highlights
Today, we're announcing **Qwen3-Coder-Next-FP8**, an open-weight language model designed specifically for coding agents and local development. It features the following key enhancements:
- **Super Efficient with Significant Performance**: With only 3B activated parameters (80B ... | [
{
"start": 2,
"end": 22,
"text": "Qwen3-Coder-Next-FP8",
"label": "benchmark name",
"score": 0.9087907075881958
},
{
"start": 65,
"end": 85,
"text": "Qwen3-Coder-Next-FP8",
"label": "benchmark name",
"score": 0.9516085982322693
},
{
"start": 898,
"end": 909,
... |
mradermacher/Oniq-Home_V1-GGUF | mradermacher | 2025-09-04T06:40:03Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"en",
"base_model:Asaadzx/Oniq-Home_V1",
"base_model:quantized:Asaadzx/Oniq-Home_V1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-04T06:21:55Z | ## 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 qu... | [
{
"start": 359,
"end": 371,
"text": "Oniq-Home_V1",
"label": "benchmark name",
"score": 0.659371554851532
},
{
"start": 508,
"end": 525,
"text": "Oniq-Home_V1-GGUF",
"label": "benchmark name",
"score": 0.7323520183563232
},
{
"start": 1221,
"end": 1238,
"t... |
cturan/MiniMax-M2-GGUF | cturan | 2025-10-29T15:00:39Z | 464 | 15 | transformers | [
"transformers",
"gguf",
"text-generation",
"base_model:MiniMaxAI/MiniMax-M2",
"base_model:quantized:MiniMaxAI/MiniMax-M2",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-10-28T17:22:15Z | # Building and Running the Experimental `minimax` Branch of `llama.cpp`
**Note:**
This setup is experimental. The `minimax` branch will not work with the standard `llama.cpp`. Use it only for testing GGUF models with experimental features.
---
## System Requirements (you can use any supported this is for ubuntu bu... | [] |
mradermacher/MimicLlama-3.1-8B-DPO-GGUF | mradermacher | 2025-09-07T01:00:11Z | 9 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"dpo",
"en",
"base_model:agg-shambhavi/MimicLlama-3.1-8B-DPO",
"base_model:quantized:agg-shambhavi/MimicLlama-3.1-8B-DPO",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-06T23:50:53Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [
{
"start": 365,
"end": 386,
"text": "MimicLlama-3.1-8B-DPO",
"label": "benchmark name",
"score": 0.6552001237869263
},
{
"start": 523,
"end": 549,
"text": "MimicLlama-3.1-8B-DPO-GGUF",
"label": "benchmark name",
"score": 0.6954365968704224
}
] |
mradermacher/031-swallow-8b-0.5-base-v2new-dpo405b-i1-GGUF | mradermacher | 2025-12-25T19:15:38Z | 345 | 1 | transformers | [
"transformers",
"gguf",
"ja",
"en",
"base_model:shisa-ai/031-swallow-8b-0.5-base-v2new-dpo405b",
"base_model:quantized:shisa-ai/031-swallow-8b-0.5-base-v2new-dpo405b",
"license:llama3.3",
"license:gemma",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-08-31T22:56:02Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
ChuGyouk/F_R19_1_T1 | ChuGyouk | 2026-03-29T01:47:46Z | 385 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"unsloth",
"conversational",
"base_model:ChuGyouk/F_R19_1",
"base_model:finetune:ChuGyouk/F_R19_1",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-28T17:55:56Z | # Model Card for F_R19_1_T1
This model is a fine-tuned version of [ChuGyouk/F_R19_1](https://huggingface.co/ChuGyouk/F_R19_1).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to t... | [] |
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