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---
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
---
# 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
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