facebookresearch / facebookresearch/blt
Integration with HF: tokenizer
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Description
Hey there!
I'm following up on the discussion about tokenization in a recent PR. @EntilZha
So I've made a byte tokenizer fully compatible with transformers.
It does the obvious byte encoding and it can leverage all the handy tools from its parents:
- padding / truncation with various options
- applying chat templates
- etc
I've made a small demo in Google Colab to show the usual stuff.
You could implement the patching logic in a subclass too.
BTW I love BLT, it makes so much sense!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the discussion in PR 98, the proposed changes in the Hugging Face transformers PR 36216, and the linked Colab demo. Define the integration surface and expected tokenizer behavior from those references; done should mean BLT's tokenizer is compatible with transformers and supports the listed padding, truncation, and chat-template features.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface, python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100