Instructions to use annedirkson/BERT_embeddings_ADR_normalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annedirkson/BERT_embeddings_ADR_normalization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="annedirkson/BERT_embeddings_ADR_normalization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("annedirkson/BERT_embeddings_ADR_normalization") model = AutoModel.from_pretrained("annedirkson/BERT_embeddings_ADR_normalization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sparse_encoder.pk from annedirkson/BERT_embeddings_ADR_normalization: direct link, hf CLI and curl.
- Browser
- Download file 21.7 kB
-
https://huggingface.co/annedirkson/BERT_embeddings_ADR_normalization/resolve/main/sparse_encoder.pk
- Command line
-
hf download hf://annedirkson/BERT_embeddings_ADR_normalization/sparse_encoder.pk
-
curl -L -o sparse_encoder.pk https://huggingface.co/annedirkson/BERT_embeddings_ADR_normalization/resolve/main/sparse_encoder.pk
21.7 kB
This file contains binary data. It cannot be displayed, but you can still download it.