
# 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](https://github.com/huggingface/pytorch-image-models/network/dependents)
tab on GitHub.

### Package & Repository star count

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


Package             |  Repository
:-------------------------:|:-------------------------:
![pytorch-image-models-dependent package star count](./pytorch-image-models-dependents/resolve/main/pytorch-image-models-dependent_package_star_count.png)  |  ![pytorch-image-models-dependent repository star count](./pytorch-image-models-dependents/resolve/main/pytorch-image-models-dependent_repository_star_count.png)

There are 18 packages that have more than 1000 stars.

There are 39 repositories that have more than 1000 stars.


The top 10 in each category are the following:

*Package*

[huggingface/transformers](https://github.com/huggingface/transformers): 70536

[fastai/fastai](https://github.com/fastai/fastai): 22776

[open-mmlab/mmdetection](https://github.com/open-mmlab/mmdetection): 21390

[MVIG-SJTU/AlphaPose](https://github.com/MVIG-SJTU/AlphaPose): 6424

[qubvel/segmentation_models.pytorch](https://github.com/qubvel/segmentation_models.pytorch): 6115

[awslabs/autogluon](https://github.com/awslabs/autogluon): 4818

[neuml/txtai](https://github.com/neuml/txtai): 2531

[open-mmlab/mmaction2](https://github.com/open-mmlab/mmaction2): 2357

[open-mmlab/mmselfsup](https://github.com/open-mmlab/mmselfsup): 2271

[lukas-blecher/LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR): 1999

*Repository*

[huggingface/transformers](https://github.com/huggingface/transformers): 70536

[commaai/openpilot](https://github.com/commaai/openpilot): 35919

[facebookresearch/detectron2](https://github.com/facebookresearch/detectron2): 22287

[ray-project/ray](https://github.com/ray-project/ray): 22057

[open-mmlab/mmdetection](https://github.com/open-mmlab/mmdetection): 21390

[NVIDIA/DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples): 9260

[microsoft/unilm](https://github.com/microsoft/unilm): 6664

[pytorch/tutorials](https://github.com/pytorch/tutorials): 6331

[qubvel/segmentation_models.pytorch](https://github.com/qubvel/segmentation_models.pytorch): 6115

[hpcaitech/ColossalAI](https://github.com/hpcaitech/ColossalAI): 4944


### Package & Repository fork count

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

Package             |  Repository
:-------------------------:|:-------------------------:
![pytorch-image-models-dependent package forks count](./pytorch-image-models-dependents/resolve/main/pytorch-image-models-dependent_package_forks_count.png)  |  ![pytorch-image-models-dependent repository forks count](./pytorch-image-models-dependents/resolve/main/pytorch-image-models-dependent_repository_forks_count.png)

There are 12 packages that have more than 200 forks.

There are 28 repositories that have more than 200 forks.


The top 10 in each category are the following:

*Package*

[huggingface/transformers](https://github.com/huggingface/transformers): 16175

[open-mmlab/mmdetection](https://github.com/open-mmlab/mmdetection): 7791

[fastai/fastai](https://github.com/fastai/fastai): 7296

[MVIG-SJTU/AlphaPose](https://github.com/MVIG-SJTU/AlphaPose): 1765

[qubvel/segmentation_models.pytorch](https://github.com/qubvel/segmentation_models.pytorch): 1217

[open-mmlab/mmaction2](https://github.com/open-mmlab/mmaction2): 787

[awslabs/autogluon](https://github.com/awslabs/autogluon): 638

[open-mmlab/mmselfsup](https://github.com/open-mmlab/mmselfsup): 321

[rwightman/efficientdet-pytorch](https://github.com/rwightman/efficientdet-pytorch): 265

[lukas-blecher/LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR): 247

*Repository*

[huggingface/transformers](https://github.com/huggingface/transformers): 16175

[open-mmlab/mmdetection](https://github.com/open-mmlab/mmdetection): 7791

[commaai/openpilot](https://github.com/commaai/openpilot): 6603

[facebookresearch/detectron2](https://github.com/facebookresearch/detectron2): 6033

[ray-project/ray](https://github.com/ray-project/ray): 3879

[pytorch/tutorials](https://github.com/pytorch/tutorials): 3478

[NVIDIA/DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples): 2499

[microsoft/unilm](https://github.com/microsoft/unilm): 1223

[qubvel/segmentation_models.pytorch](https://github.com/qubvel/segmentation_models.pytorch): 1217

[layumi/Person_reID_baseline_pytorch](https://github.com/layumi/Person_reID_baseline_pytorch): 928

    
license:apache-2.0 github-stars region:us
{"license": "apache-2.0", "pretty_name": "pytorch-image-models metrics", "tags": ["github-stars"], "dataset_info": {"features": [{"name": "name", "dtype": "null"}, {"name": "stars", "dtype": "null"}, {"name": "forks", "dtype": "null"}], "splits": [{"name": "package"}, {"name": "repository"}], "download_size": 1798, "dataset_size": 0}}
TAGS
#license-apache-2.0 #github-stars #region-us 

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.



There are 18 packages that have more than 1000 stars.


There are 39 repositories that have more than 1000 stars.


The top 10 in each category are the following:


*Package*


huggingface/transformers: 70536


fastai/fastai: 22776


open-mmlab/mmdetection: 21390


MVIG-SJTU/AlphaPose: 6424


qubvel/segmentation\_models.pytorch: 6115


awslabs/autogluon: 4818


neuml/txtai: 2531


open-mmlab/mmaction2: 2357


open-mmlab/mmselfsup: 2271


lukas-blecher/LaTeX-OCR: 1999


*Repository*


huggingface/transformers: 70536


commaai/openpilot: 35919


facebookresearch/detectron2: 22287


ray-project/ray: 22057


open-mmlab/mmdetection: 21390


NVIDIA/DeepLearningExamples: 9260


microsoft/unilm: 6664


pytorch/tutorials: 6331


qubvel/segmentation\_models.pytorch: 6115


hpcaitech/ColossalAI: 4944


### Package & Repository fork count


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



There are 12 packages that have more than 200 forks.


There are 28 repositories that have more than 200 forks.


The top 10 in each category are the following:


*Package*


huggingface/transformers: 16175


open-mmlab/mmdetection: 7791


fastai/fastai: 7296


MVIG-SJTU/AlphaPose: 1765


qubvel/segmentation\_models.pytorch: 1217


open-mmlab/mmaction2: 787


awslabs/autogluon: 638


open-mmlab/mmselfsup: 321


rwightman/efficientdet-pytorch: 265


lukas-blecher/LaTeX-OCR: 247


*Repository*


huggingface/transformers: 16175


open-mmlab/mmdetection: 7791


commaai/openpilot: 6603


facebookresearch/detectron2: 6033


ray-project/ray: 3879


pytorch/tutorials: 3478


NVIDIA/DeepLearningExamples: 2499


microsoft/unilm: 1223


qubvel/segmentation\_models.pytorch: 1217


layumi/Person\_reID\_baseline\_pytorch: 928



### Package & Repository star count


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



There are 18 packages that have more than 1000 stars.


There are 39 repositories that have more than 1000 stars.


The top 10 in each category are the following:


*Package*


huggingface/transformers: 70536


fastai/fastai: 22776


open-mmlab/mmdetection: 21390


MVIG-SJTU/AlphaPose: 6424


qubvel/segmentation\_models.pytorch: 6115


awslabs/autogluon: 4818


neuml/txtai: 2531


open-mmlab/mmaction2: 2357


open-mmlab/mmselfsup: 2271


lukas-blecher/LaTeX-OCR: 1999


*Repository*


huggingface/transformers: 70536


commaai/openpilot: 35919


facebookresearch/detectron2: 22287


ray-project/ray: 22057


open-mmlab/mmdetection: 21390


NVIDIA/DeepLearningExamples: 9260


microsoft/unilm: 6664


pytorch/tutorials: 6331


qubvel/segmentation\_models.pytorch: 6115


hpcaitech/ColossalAI: 4944 ### Package & Repository fork count


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



There are 12 packages that have more than 200 forks.


There are 28 repositories that have more than 200 forks.


The top 10 in each category are the following:


*Package*


huggingface/transformers: 16175


open-mmlab/mmdetection: 7791


fastai/fastai: 7296


MVIG-SJTU/AlphaPose: 1765


qubvel/segmentation\_models.pytorch: 1217


open-mmlab/mmaction2: 787


awslabs/autogluon: 638


open-mmlab/mmselfsup: 321


rwightman/efficientdet-pytorch: 265


lukas-blecher/LaTeX-OCR: 247


*Repository*


huggingface/transformers: 16175


open-mmlab/mmdetection: 7791


commaai/openpilot: 6603


facebookresearch/detectron2: 6033


ray-project/ray: 3879


pytorch/tutorials: 3478


NVIDIA/DeepLearningExamples: 2499


microsoft/unilm: 1223


qubvel/segmentation\_models.pytorch: 1217


layumi/Person\_reID\_baseline\_pytorch: 928
TAGS
#license-apache-2.0 #github-stars #region-us 
 ### Package & Repository star count


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



There are 18 packages that have more than 1000 stars.


There are 39 repositories that have more than 1000 stars.


The top 10 in each category are the following:


*Package*


huggingface/transformers: 70536


fastai/fastai: 22776


open-mmlab/mmdetection: 21390


MVIG-SJTU/AlphaPose: 6424


qubvel/segmentation\_models.pytorch: 6115


awslabs/autogluon: 4818


neuml/txtai: 2531


open-mmlab/mmaction2: 2357


open-mmlab/mmselfsup: 2271


lukas-blecher/LaTeX-OCR: 1999


*Repository*


huggingface/transformers: 70536


commaai/openpilot: 35919


facebookresearch/detectron2: 22287


ray-project/ray: 22057


open-mmlab/mmdetection: 21390


NVIDIA/DeepLearningExamples: 9260


microsoft/unilm: 6664


pytorch/tutorials: 6331


qubvel/segmentation\_models.pytorch: 6115


hpcaitech/ColossalAI: 4944 ### Package & Repository fork count


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



There are 12 packages that have more than 200 forks.


There are 28 repositories that have more than 200 forks.


The top 10 in each category are the following:


*Package*


huggingface/transformers: 16175


open-mmlab/mmdetection: 7791


fastai/fastai: 7296


MVIG-SJTU/AlphaPose: 1765


qubvel/segmentation\_models.pytorch: 1217


open-mmlab/mmaction2: 787


awslabs/autogluon: 638


open-mmlab/mmselfsup: 321


rwightman/efficientdet-pytorch: 265


lukas-blecher/LaTeX-OCR: 247


*Repository*


huggingface/transformers: 16175


open-mmlab/mmdetection: 7791


commaai/openpilot: 6603


facebookresearch/detectron2: 6033


ray-project/ray: 3879


pytorch/tutorials: 3478


NVIDIA/DeepLearningExamples: 2499


microsoft/unilm: 1223


qubvel/segmentation\_models.pytorch: 1217


layumi/Person\_reID\_baseline\_pytorch: 928