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evaluate-0.4.0
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مشاهده بیشترتوضیحات
HuggingFace community-driven open-source library of evaluation
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | evaluate-0.4.0 |
| نام | evaluate |
| نسخه کتابخانه | 0.4.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | HuggingFace Inc. |
| ایمیل نویسنده | leandro@huggingface.co |
| آدرس صفحه اصلی | https://github.com/huggingface/evaluate |
| آدرس اینترنتی | https://pypi.org/project/evaluate/ |
| مجوز | Apache 2.0 |
<p align="center">
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<img src="https://huggingface.co/datasets/evaluate/media/resolve/main/evaluate-banner.png" width="400"/>
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</p>
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<a href="https://huggingface.co/docs/evaluate/index">
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</a>
<a href="https://github.com/huggingface/evaluate/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/evaluate.svg">
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<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-2.0-4baaaa.svg">
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🤗 Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized.
It currently contains:
- **implementations of dozens of popular metrics**: the existing metrics cover a variety of tasks spanning from NLP to Computer Vision, and include dataset-specific metrics for datasets. With a simple command like `accuracy = load("accuracy")`, get any of these metrics ready to use for evaluating a ML model in any framework (Numpy/Pandas/PyTorch/TensorFlow/JAX).
- **comparisons and measurements**: comparisons are used to measure the difference between models and measurements are tools to evaluate datasets.
- **an easy way of adding new evaluation modules to the 🤗 Hub**: you can create new evaluation modules and push them to a dedicated Space in the 🤗 Hub with `evaluate-cli create [metric name]`, which allows you to see easily compare different metrics and their outputs for the same sets of references and predictions.
[🎓 **Documentation**](https://huggingface.co/docs/evaluate/)
🔎 **Find a [metric](https://huggingface.co/evaluate-metric), [comparison](https://huggingface.co/evaluate-comparison), [measurement](https://huggingface.co/evaluate-measurement) on the Hub**
[🌟 **Add a new evaluation module**](https://huggingface.co/docs/evaluate/)
🤗 Evaluate also has lots of useful features like:
- **Type checking**: the input types are checked to make sure that you are using the right input formats for each metric
- **Metric cards**: each metrics comes with a card that describes the values, limitations and their ranges, as well as providing examples of their usage and usefulness.
- **Community metrics:** Metrics live on the Hugging Face Hub and you can easily add your own metrics for your project or to collaborate with others.
# Installation
## With pip
🤗 Evaluate can be installed from PyPi and has to be installed in a virtual environment (venv or conda for instance)
```bash
pip install evaluate
```
# Usage
🤗 Evaluate's main methods are:
- `evaluate.list_evaluation_modules()` to list the available metrics, comparisons and measurements
- `evaluate.load(module_name, **kwargs)` to instantiate an evaluation module
- `results = module.compute(*kwargs)` to compute the result of an evaluation module
# Adding a new evaluation module
First install the necessary dependencies to create a new metric with the following command:
```bash
pip install evaluate[template]
```
Then you can get started with the following command which will create a new folder for your metric and display the necessary steps:
```bash
evaluate-cli create "Awesome Metric"
```
See this [step-by-step guide](https://huggingface.co/docs/evaluate/creating_and_sharing) in the documentation for detailed instructions.
## Credits
Thanks to [@marella](https://github.com/marella) for letting us use the `evaluate` namespace on PyPi previously used by his [library](https://github.com/marella/evaluate).
نیازمندی
| مقدار | نام |
|---|---|
| >=2.0.0 | datasets |
| >=1.17 | numpy |
| - | dill |
| - | pandas |
| >=2.19.0 | requests |
| >=4.62.1 | tqdm |
| - | xxhash |
| - | multiprocess |
| >=2021.05.0 | fsspec[http] |
| >=0.7.0 | huggingface-hub |
| - | packaging |
| <0.19 | responses |
| - | importlib-metadata |
| - | absl-py |
| >=1.1.1 | charcut |
| >=1.2.0 | cer |
| - | nltk |
| - | pytest |
| - | pytest-datadir |
| - | pytest-xdist |
| !=2.6.0,!=2.6.1,<=2.10,>=2.3 | tensorflow |
| - | torch |
| >=0.3.6 | bert-score |
| >=0.1.2 | rouge-score |
| - | sacrebleu |
| - | sacremoses |
| - | scipy |
| - | seqeval |
| - | scikit-learn |
| - | jiwer |
| - | sentencepiece |
| - | transformers |
| - | mauve-text |
| - | trectools |
| >=0.10.1 | toml |
| >=1.5.1 | requests-file |
| >=3.1.0 | tldextract |
| >=1.6.3 | texttable |
| >=1.3.4 | unidecode |
| >=1.0.1 | Werkzeug |
| ~=1.15.0 | six |
| ~=22.0 | black |
| >=3.8.3 | flake8 |
| >=5.0.0 | isort |
| >=5.3.1 | pyyaml |
| - | s3fs |
| - | transformers |
| >=1.7.1 | scipy |
| ~=22.0 | black |
| >=3.8.3 | flake8 |
| >=5.0.0 | isort |
| >=5.3.1 | pyyaml |
| - | cookiecutter |
| >=3.0.0 | gradio |
| !=2.6.0,!=2.6.1,>=2.2.0 | tensorflow |
| !=2.6.0,!=2.6.1,>=2.2.0 | tensorflow-gpu |
| - | absl-py |
| >=1.1.1 | charcut |
| >=1.2.0 | cer |
| - | nltk |
| - | pytest |
| - | pytest-datadir |
| - | pytest-xdist |
| !=2.6.0,!=2.6.1,<=2.10,>=2.3 | tensorflow |
| - | torch |
| >=0.3.6 | bert-score |
| >=0.1.2 | rouge-score |
| - | sacrebleu |
| - | sacremoses |
| - | scipy |
| - | seqeval |
| - | scikit-learn |
| - | jiwer |
| - | sentencepiece |
| - | transformers |
| - | mauve-text |
| - | trectools |
| >=0.10.1 | toml |
| >=1.5.1 | requests-file |
| >=3.1.0 | tldextract |
| >=1.6.3 | texttable |
| >=1.3.4 | unidecode |
| >=1.0.1 | Werkzeug |
| ~=1.15.0 | six |
| - | torch |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7.0 | Python |
نحوه نصب
نصب پکیج whl evaluate-0.4.0:
pip install evaluate-0.4.0.whl
نصب پکیج tar.gz evaluate-0.4.0:
pip install evaluate-0.4.0.tar.gz