c82e017aa9
1. Fixes evaluation errors popping up when you train/eval on squad v2 (one was newly encountered and one that was previously reported Running SQuAD 1.0 sample command raises IndexError #15401 but not completely fixed). 2. Removes boolean arguments that don't use store_true. Please, don't use these: *ANY non-empty string is being converted to True in this case and this clearly is not the desired behavior (and it creates a LOT of confusion). 3. All no-trainer test scripts are now saving metric values in the same way (with the right prefix eval_), which is consistent with the trainer-based versions. 4. Adds forgotten model.eval() in the no-trainer versions. This improved some results, but not everything (see the discussion in the end). Please, see the F1 scores and the discussion below. |
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| .. | ||
| flax | ||
| legacy | ||
| pytorch | ||
| research_projects | ||
| tensorflow | ||
| README.md | ||
Examples
We host a wide range of example scripts for multiple learning frameworks. Simply choose your favorite: TensorFlow, PyTorch or JAX/Flax.
We also have some research projects, as well as some legacy examples. Note that unlike the main examples these are not actively maintained, and may require specific older versions of dependencies in order to run.
While we strive to present as many use cases as possible, the example scripts are just that - examples. It is expected that they won't work out-of-the box on your specific problem and that you will be required to change a few lines of code to adapt them to your needs. To help you with that, most of the examples fully expose the preprocessing of the data, allowing you to tweak and edit them as required.
Please discuss on the forum or in an issue a feature you would like to implement in an example before submitting a PR; we welcome bug fixes, but since we want to keep the examples as simple as possible it's unlikely that we will merge a pull request adding more functionality at the cost of readability.
Important note
Important
To make sure you can successfully run the latest versions of the example scripts, you have to install the library from source and install some example-specific requirements. To do this, execute the following steps in a new virtual environment:
git clone https://github.com/huggingface/transformers
cd transformers
pip install .
Then cd in the example folder of your choice and run
pip install -r requirements.txt
To browse the examples corresponding to released versions of 🤗 Transformers, click on the line below and then on your desired version of the library:
Examples for older versions of 🤗 Transformers
Alternatively, you can switch your cloned 🤗 Transformers to a specific version (for instance with v3.5.1) with
git checkout tags/v3.5.1
and run the example command as usual afterward.