Description

This is the dataset repository used in the pyiqa toolbox. Please refer to Awesome Image Quality Assessment for details of each dataset Example commandline script with huggingface-cli: huggingface-cli download chaofengc/IQA-PyTorch-Datasets live.tgz --local-dir ./datasets --repo-type dataset cd datasets tar -xzvf live.tgz

  Disclaimer for This Dataset Collection

This collection of datasets is compiled and maintained for academic, research, and educational… See the full description on the dataset page: https://huggingface.co/datasets/chaofengc/IQA-PyTorch-Datasets.

forked from https://github.com/huggingface/transformers

pytorch-image-models metrics

This dataset contains metrics about the huggingface/pytorch-image-models package. Number of repositories in the dataset: 3615 Number of packages in the dataset: 89

  Package dependents

This contains the data available in the used-by tab on GitHub.

  Package & Repository star count

This section shows the package and repository star count, individually.

Package Repository

There are 18 packages that have more than 1000… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/pytorch-image-models-dependents.

Dataset

This dataset was created by Megha Kapoor

Contents

i44p/dped-pytorch dataset hosted on Hugging Face and contributed by the HF Datasets community

!python -m pip install --upgrade /kaggle/input/pytorchhuggingface-wheels-cuda-116/*.whl

The SloNER is a model for Slovenian Named Entity Recognition. It is is a PyTorch neural network model, intended for usage with the HuggingFace transformers library (https://github.com/huggingface/transformers).

The model is based on the Slovenian RoBERTa contextual embeddings model SloBERTa 2.0 (http://hdl.handle.net/11356/1397). The model was trained on the SUK 1.0 training corpus (http://hdl.handle.net/11356/1747).The source code of the model is available on GitHub repository https://github.com/clarinsi/SloNER.

Deberta v3 PyTorch model from huggingface:

https://huggingface.co/microsoft/deberta-v3-base/tree/main

Meant to be used for competitions where internet access is disallowed.

pytorch-survival/gene_annotations dataset hosted on Hugging Face and contributed by the HF Datasets community

kye/all-pytorch-code dataset hosted on Hugging Face and contributed by the HF Datasets community

Context

Accelerate is a Python library that allows running raw PyTorch training scripts on any kind of device very easily. It allows easy integration into your code. More details are here - https://huggingface.co/blog/accelerate-library

Crayon2023/pytorch-llama dataset hosted on Hugging Face and contributed by the HF Datasets community

!python -m pip install --upgrade /kaggle/input/pytorchhuggingface-wheels/*.whl

To import pretrained transformer weights, simply specify the path in the corresponding function: model_path = '../input/transformers/roberta-base' model = AutoModel.from_pretrained(model_path) See this notebook for a more detailed example.

The dataset includes the following weights, configs and tokenizers: - albert-large-v2 - bert-base-uncased - bert-large-uncased - distilroberta-base - distilbert-base-uncased - google/electra-base-discriminator - facebook/bart-base - facebook/bart-large - funnel-transformer/small - funnel-transformer/large - roberta-base - roberta-large - t5-base - t5-large - xlnet-base-cased - xlnet-large-cased

All files are downloaded from Huggingface Model Hub at https://huggingface.co/models. License: Apache License 2.0

Full repository cloned from fix #497 · huggingface/pytorch-pretrained-BERT@929579f

Description

This repo contains the meta information of datasets stored in chaofengc/IQA-PyTorch-Weights. They are used in the training codes of the pyiqa toolbox.

  Disclaimer for Datasets Included

This collection of datasets is compiled and maintained for academic, research, and educational purposes. It is important to note the following points regarding the datasets included in this Collection:

Rights & Permissions: Each dataset in this Collection is the property of its… See the full description on the dataset page: https://huggingface.co/datasets/chaofengc/IQA-PyTorch-Datasets-metainfo.

kye/pytorch-repo-code dataset hosted on Hugging Face and contributed by the HF Datasets community

Crayon2023/pytorch-Qwen-7B dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset Card for "ARTeFACT"

ARTeFACT: Benchmarking Segmentation Models on Diverse Analogue Media Damage

Here we provide example code for downloading the data, loading it as a PyTorch dataset, splitting by material and/or content, and visualising examples.

  Housekeeping

!pip install datasets !pip install -qqqU wandb transformers pytorch-lightning==1.9.2 albumentations torchmetrics torchinfo !pip install -qqq requests gradio

import os from glob import glob

import cv2… See the full description on the dataset page: https://huggingface.co/datasets/danielaivanova/damaged-media.

Dataset

This dataset was created by RAHUL BAJAJ

Contents