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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75a74ec141d7b9a18bf2e6cc0b7e10309c88f1e907984d02139f3d788c9f488d
- Size of remote file:
- 31.7 MB
- SHA256:
- 002146d5baf5a9676c0748993d7ec275f0e991ca6bd4664ff8c7644d902f77fd
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