Instructions to use EMBO/bert-base-cased_NER-task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBO/bert-base-cased_NER-task with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EMBO/bert-base-cased_NER-task")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EMBO/bert-base-cased_NER-task") model = AutoModelForTokenClassification.from_pretrained("EMBO/bert-base-cased_NER-task", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from EMBO/bert-base-cased_NER-task: direct link, hf CLI and curl.
- Browser
- Download file 862 MB
-
https://huggingface.co/EMBO/bert-base-cased_NER-task/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://EMBO/bert-base-cased_NER-task/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/EMBO/bert-base-cased_NER-task/resolve/main/last-checkpoint/optimizer.pt
862 MB
- Xet hash:
- be0666f8e62b5c1c3abf2ef68a8be754d433a8ea26e4ec2ed5e212fe815e95ce
- Size of remote file:
- 862 MB
- SHA256:
- 0955c1d3b650c9c643c7f2178954f57982b9878d21c7ba1e5fef1f25104b7e68
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