Many models have identical implementations of prune_heads it would be nice to store that implementation as a method on PretrainedModel and reduce the redundancy.

Spacy has customizable word level tokenizers with rules for multiple languages. I think porting that to rust would add nicely to this package. Having a customizable uniform word level tokenization across platforms (client web, server) and languages would be beneficial. Currently, idk any clean way or whether it's even possible to write bindings for spacy cython.

Spacy Tokenizer Code

https:

Currently, we are not logging macro/micro averages on Tensorboard since it was appearing strangely in the interface (picture below), so it was removed.

Add macro/micro to Tensorboard.

I'm playing around with this wonderful code but I'm running into a curious issue when I try to train the model with my own data.

I replicated the personachat_self_original.json file structure and added my own data. I deleted dataset_cache_OpenAIGPTTokenizer file but when I try to train, I get this error:

INFO:train.py:Pad inputs and convert to Tensor
Traceback (most recent call last)

Running a current mypy on mkosi gives the following warnings

mkosi:968: error: Argument 1 to "partition" has incompatible type "Optional[str]"; expected "str"
mkosi:971: error: Argument 1 to "partition" has incompatible type "Optional[str]"; expected "str"
mkosi:4624: error: "Dict[str, CommandLineArguments]" has no attribute "director

The last line is harmless and addressed in #36

Describe the bug
When using the LMFineTuner and specifying the learning_rate_finder_configs , an error is thrown when passing these configs to finetuner.find_learning_rate() as suggested in the documentation and in the [Colab example](https://colab.research.google.com/github/Novetta/adaptnlp/blob/master/tutor

• add list of people that have contributed anyhow to the project to readme.md
• show contributors under the npm 'collaborators' block (just read-only, people should not have write access, not sure if this is possible).

If you try to render ads without an ad unit path being present either in the global config or slot config, react-prebid will happily try to initialize GPT slots, prompting an error from the gpt.js library, e.g.:

Exception in queued GPT command TypeError: "slot is null"

Validate if an ad unit path is provided and give the developers a useful error message in this case.

There needs to be detailed instructions as to how this library can be integrated into the Arduino software.