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evaluate-dependents

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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