
# evaluate metrics

This dataset contains metrics about the huggingface/evaluate package.

Number of repositories in the dataset: 106
Number of packages in the dataset: 3

## Package dependents

This contains the data available in the [used-by](https://github.com/huggingface/evaluate/network/dependents)
tab on GitHub.

### Package & Repository star count

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


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

There are 1 packages that have more than 1000 stars.

There are 2 repositories that have more than 1000 stars.


The top 10 in each category are the following:

*Package*

[huggingface/accelerate](https://github.com/huggingface/accelerate): 2884

[fcakyon/video-transformers](https://github.com/fcakyon/video-transformers): 4

[entelecheia/ekorpkit](https://github.com/entelecheia/ekorpkit): 2

*Repository*

[huggingface/transformers](https://github.com/huggingface/transformers): 70481

[huggingface/accelerate](https://github.com/huggingface/accelerate): 2884

[huggingface/evaluate](https://github.com/huggingface/evaluate): 878

[pytorch/benchmark](https://github.com/pytorch/benchmark): 406

[imhuay/studies](https://github.com/imhuay/studies): 161

[AIRC-KETI/ke-t5](https://github.com/AIRC-KETI/ke-t5): 128

[Jaseci-Labs/jaseci](https://github.com/Jaseci-Labs/jaseci): 32

[philschmid/optimum-static-quantization](https://github.com/philschmid/optimum-static-quantization): 20

[hms-dbmi/scw](https://github.com/hms-dbmi/scw): 19

[philschmid/optimum-transformers-optimizations](https://github.com/philschmid/optimum-transformers-optimizations): 15

[girafe-ai/msai-python](https://github.com/girafe-ai/msai-python): 15

[lewtun/dl4phys](https://github.com/lewtun/dl4phys): 15


### Package & Repository fork count

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

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

There are 1 packages that have more than 200 forks.

There are 2 repositories that have more than 200 forks.


The top 10 in each category are the following:

*Package*

[huggingface/accelerate](https://github.com/huggingface/accelerate): 224

[fcakyon/video-transformers](https://github.com/fcakyon/video-transformers): 0

[entelecheia/ekorpkit](https://github.com/entelecheia/ekorpkit): 0

*Repository*

[huggingface/transformers](https://github.com/huggingface/transformers): 16157

[huggingface/accelerate](https://github.com/huggingface/accelerate): 224

[pytorch/benchmark](https://github.com/pytorch/benchmark): 131

[Jaseci-Labs/jaseci](https://github.com/Jaseci-Labs/jaseci): 67

[huggingface/evaluate](https://github.com/huggingface/evaluate): 48

[imhuay/studies](https://github.com/imhuay/studies): 42

[AIRC-KETI/ke-t5](https://github.com/AIRC-KETI/ke-t5): 14

[girafe-ai/msai-python](https://github.com/girafe-ai/msai-python): 14

[hms-dbmi/scw](https://github.com/hms-dbmi/scw): 11

[kili-technology/automl](https://github.com/kili-technology/automl): 5

[whatofit/LevelWordWithFreq](https://github.com/whatofit/LevelWordWithFreq): 5

    
license:apache-2.0 github-stars region:us
{"license": "apache-2.0", "pretty_name": "evaluate metrics", "tags": ["github-stars"], "dataset_info": {"features": [{"name": "name", "dtype": "string"}, {"name": "stars", "dtype": "int64"}, {"name": "forks", "dtype": "int64"}], "splits": [{"name": "package", "num_bytes": 1830, "num_examples": 45}, {"name": "repository", "num_bytes": 54734, "num_examples": 1161}], "download_size": 37570, "dataset_size": 56564}}
TAGS
#license-apache-2.0 #github-stars #region-us 

evaluate metrics
================


This dataset contains metrics about the huggingface/evaluate package.


Number of repositories in the dataset: 106
Number of packages in the dataset: 3


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 1 packages that have more than 1000 stars.


There are 2 repositories that have more than 1000 stars.


The top 10 in each category are the following:


*Package*


huggingface/accelerate: 2884


fcakyon/video-transformers: 4


entelecheia/ekorpkit: 2


*Repository*


huggingface/transformers: 70481


huggingface/accelerate: 2884


huggingface/evaluate: 878


pytorch/benchmark: 406


imhuay/studies: 161


AIRC-KETI/ke-t5: 128


Jaseci-Labs/jaseci: 32


philschmid/optimum-static-quantization: 20


hms-dbmi/scw: 19


philschmid/optimum-transformers-optimizations: 15


girafe-ai/msai-python: 15


lewtun/dl4phys: 15


### Package & Repository fork count


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



There are 1 packages that have more than 200 forks.


There are 2 repositories that have more than 200 forks.


The top 10 in each category are the following:


*Package*


huggingface/accelerate: 224


fcakyon/video-transformers: 0


entelecheia/ekorpkit: 0


*Repository*


huggingface/transformers: 16157


huggingface/accelerate: 224


pytorch/benchmark: 131


Jaseci-Labs/jaseci: 67


huggingface/evaluate: 48


imhuay/studies: 42


AIRC-KETI/ke-t5: 14


girafe-ai/msai-python: 14


hms-dbmi/scw: 11


kili-technology/automl: 5


whatofit/LevelWordWithFreq: 5



### Package & Repository star count


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



There are 1 packages that have more than 1000 stars.


There are 2 repositories that have more than 1000 stars.


The top 10 in each category are the following:


*Package*


huggingface/accelerate: 2884


fcakyon/video-transformers: 4


entelecheia/ekorpkit: 2


*Repository*


huggingface/transformers: 70481


huggingface/accelerate: 2884


huggingface/evaluate: 878


pytorch/benchmark: 406


imhuay/studies: 161


AIRC-KETI/ke-t5: 128


Jaseci-Labs/jaseci: 32


philschmid/optimum-static-quantization: 20


hms-dbmi/scw: 19


philschmid/optimum-transformers-optimizations: 15


girafe-ai/msai-python: 15


lewtun/dl4phys: 15 ### Package & Repository fork count


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



There are 1 packages that have more than 200 forks.


There are 2 repositories that have more than 200 forks.


The top 10 in each category are the following:


*Package*


huggingface/accelerate: 224


fcakyon/video-transformers: 0


entelecheia/ekorpkit: 0


*Repository*


huggingface/transformers: 16157


huggingface/accelerate: 224


pytorch/benchmark: 131


Jaseci-Labs/jaseci: 67


huggingface/evaluate: 48


imhuay/studies: 42


AIRC-KETI/ke-t5: 14


girafe-ai/msai-python: 14


hms-dbmi/scw: 11


kili-technology/automl: 5


whatofit/LevelWordWithFreq: 5
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 1 packages that have more than 1000 stars.


There are 2 repositories that have more than 1000 stars.


The top 10 in each category are the following:


*Package*


huggingface/accelerate: 2884


fcakyon/video-transformers: 4


entelecheia/ekorpkit: 2


*Repository*


huggingface/transformers: 70481


huggingface/accelerate: 2884


huggingface/evaluate: 878


pytorch/benchmark: 406


imhuay/studies: 161


AIRC-KETI/ke-t5: 128


Jaseci-Labs/jaseci: 32


philschmid/optimum-static-quantization: 20


hms-dbmi/scw: 19


philschmid/optimum-transformers-optimizations: 15


girafe-ai/msai-python: 15


lewtun/dl4phys: 15 ### Package & Repository fork count


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



There are 1 packages that have more than 200 forks.


There are 2 repositories that have more than 200 forks.


The top 10 in each category are the following:


*Package*


huggingface/accelerate: 224


fcakyon/video-transformers: 0


entelecheia/ekorpkit: 0


*Repository*


huggingface/transformers: 16157


huggingface/accelerate: 224


pytorch/benchmark: 131


Jaseci-Labs/jaseci: 67


huggingface/evaluate: 48


imhuay/studies: 42


AIRC-KETI/ke-t5: 14


girafe-ai/msai-python: 14


hms-dbmi/scw: 11


kili-technology/automl: 5


whatofit/LevelWordWithFreq: 5