--- 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