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Load Huggingface Transformers model using TFAutoModel

See original GitHub issue

Description of Problem: I want to use models provided by the HuggingFace transformers library that are not available when using the HFTransformersNLP Component.

Overview of the Solution: Right now, models are loaded using a dictionary of architectures in rasa/nlu/utils/hugging_face/registry.py. Using the AutoModel and AutoTokenizer features from the transformers library, we can get rid of these limitations, as well as not having to define a model_name in the config file. We can only use the model_weights info to select the proper model and weights of the wanted tokenizers and featurizers.

Examples (if relevant): Docs for how to use the “auto” features is available here

Blockers (if relevant):

Definition of Done:

Changes are made to files in rasa/rasa/nlu/utils/hugging_face/
Tests are added
Feature described the docs
Feature mentioned in the changelog

Issue Analytics

State:
Created 3 years ago
Comments:10 (6 by maintainers)

Top GitHub Comments

1reaction

Ghostvvcommented, Mar 17, 2022

Exalate commented:

Ghostvv commented:

shall we move it to blocked then?

0reactions

sync-by-unito[bot]commented, Dec 19, 2022

➤ Maxime Verger commented:

💡 Heads up! We’re moving issues to Jira: https://rasa-open-source.atlassian.net/browse/OSS.

From now on, this Jira board is the place where you can browse (without an account) and create issues (you’ll need a free Jira account for that). This GitHub issue has already been migrated to Jira and will be closed on January 9th, 2023. Do not forget to subscribe to the corresponding Jira issue!

➡️ More information in the forum: https://forum.rasa.com/t/migration-of-rasa-oss-issues-to-jira/56569.

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