Instructions to use aehrm/dtaec-type-normalizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aehrm/dtaec-type-normalizer with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="aehrm/dtaec-type-normalizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("aehrm/dtaec-type-normalizer") model = AutoModelForSeq2SeqLM.from_pretrained("aehrm/dtaec-type-normalizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fdaff8aa92baebbf46d59da9885d31dc7fa4e898649a15829117bf367828d28
- Size of remote file:
- 5.3 kB
- SHA256:
- 4209630a4722251c95631a073744ab4282fa18d97dd15d63b8d9b8a9c8420475
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