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---
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license: apache-2.0
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pretty_name: evaluate metrics
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tags:
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- github-stars
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---
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# evaluate metrics
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This dataset contains metrics about the huggingface/evaluate package.
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Number of repositories in the dataset: 106
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Number of packages in the dataset: 3
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## Package dependents
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This contains the data available in the [used-by](https://github.com/huggingface/evaluate/network/dependents)
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tab on GitHub.
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### Package & Repository star count
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This section shows the package and repository star count, individually.
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Package | Repository
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:-------------------------:|:-------------------------:
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![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)
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There are 1 packages that have more than 1000 stars.
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There are 2 repositories that have more than 1000 stars.
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The top 10 in each category are the following:
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*Package*
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[huggingface/accelerate](https://github.com/huggingface/accelerate): 2884
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[fcakyon/video-transformers](https://github.com/fcakyon/video-transformers): 4
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[entelecheia/ekorpkit](https://github.com/entelecheia/ekorpkit): 2
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*Repository*
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[huggingface/transformers](https://github.com/huggingface/transformers): 70481
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[huggingface/accelerate](https://github.com/huggingface/accelerate): 2884
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[huggingface/evaluate](https://github.com/huggingface/evaluate): 878
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[pytorch/benchmark](https://github.com/pytorch/benchmark): 406
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[imhuay/studies](https://github.com/imhuay/studies): 161
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[AIRC-KETI/ke-t5](https://github.com/AIRC-KETI/ke-t5): 128
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[Jaseci-Labs/jaseci](https://github.com/Jaseci-Labs/jaseci): 32
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[philschmid/optimum-static-quantization](https://github.com/philschmid/optimum-static-quantization): 20
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[hms-dbmi/scw](https://github.com/hms-dbmi/scw): 19
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[philschmid/optimum-transformers-optimizations](https://github.com/philschmid/optimum-transformers-optimizations): 15
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[girafe-ai/msai-python](https://github.com/girafe-ai/msai-python): 15
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[lewtun/dl4phys](https://github.com/lewtun/dl4phys): 15
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### Package & Repository fork count
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This section shows the package and repository fork count, individually.
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Package | Repository
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:-------------------------:|:-------------------------:
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![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)
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There are 1 packages that have more than 200 forks.
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There are 2 repositories that have more than 200 forks.
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The top 10 in each category are the following:
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*Package*
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[huggingface/accelerate](https://github.com/huggingface/accelerate): 224
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[fcakyon/video-transformers](https://github.com/fcakyon/video-transformers): 0
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[entelecheia/ekorpkit](https://github.com/entelecheia/ekorpkit): 0
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*Repository*
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[huggingface/transformers](https://github.com/huggingface/transformers): 16157
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[huggingface/accelerate](https://github.com/huggingface/accelerate): 224
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[pytorch/benchmark](https://github.com/pytorch/benchmark): 131
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[Jaseci-Labs/jaseci](https://github.com/Jaseci-Labs/jaseci): 67
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[huggingface/evaluate](https://github.com/huggingface/evaluate): 48
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[imhuay/studies](https://github.com/imhuay/studies): 42
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[AIRC-KETI/ke-t5](https://github.com/AIRC-KETI/ke-t5): 14
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[girafe-ai/msai-python](https://github.com/girafe-ai/msai-python): 14
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[hms-dbmi/scw](https://github.com/hms-dbmi/scw): 11
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[kili-technology/automl](https://github.com/kili-technology/automl): 5
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[whatofit/LevelWordWithFreq](https://github.com/whatofit/LevelWordWithFreq): 5
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