* Add TapexTokenizer * Improve docstrings and provide option to provide answer * Remove option for pretokenized inputs * Add TAPEX to README * Fix copies * Remove option for pretokenized inputs * Initial commit: add tapex fine-tuning examples on both table-based question answering and table-based fact verification. * - Draft a README file for running the script and introducing some background. - Remove unused code lines in tabfact script. - Disable the deafult `pad_to_max_length` option which is memory-consuming. * * Support `as_target_tokenizer` function for TapexTokenizer. * Fix the do_lower_case behaviour of TapexTokenizer. * Add unit tests for target scenarios and cased/uncased scenarios for both source and target. * * Replace the label BartTokenizer with TapexTokenizer's as_target_tokenizer function. * Fix typos in tapex example README. * * fix the evaluation script - remove the property `task_name` * * Make the label space more clear for tabfact tasks * * Using a new fine-tuning script for tapex-base on tabfact. * * Remove the lowercase code outside the tokenizer - we use the tokenizer to control whether do_lower_case * Guarantee the hyper-parameter can be run without out-of-memory on 16GB card and report the new reproduced number on wikisql * * Remove the default tokenizer_name option. * Provide evaluation command. * * Support for WikiTableQuestion dataset. * Fix a typo in README. * * Fix the datasets's key name in WikiTableQuestions * Run make fixup and move test to folder * Fix quality * Apply suggestions from code review * Apply suggestions from code review Co-authored-by: Suraj Patil <surajp815@gmail.com> * Apply suggestions from code review * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Apply some more suggestions from code review * Improve docstrings * Overwrite failing test * Improve comment in example scripts * Fix rebase * Add TAPEX to Auto mapping * Add TAPEX to auto config mappings * Put TAPEX higher than BART in auto mapping * Add TAPEX to doc tests Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain> Co-authored-by: SivilTaram <qianlxc@outlook.com> Co-authored-by: Niels Rogge <nielsrogge@nielss-mbp.home> Co-authored-by: Suraj Patil <surajp815@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local> |
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| 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.