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")# 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
- Xet hash:
- a5cf6b2f3cd11699a52dbc24d1958039d069a990728d3226927b8c0285fac429
- Size of remote file:
- 3.18 kB
- SHA256:
- 11efea90b746e0f8c7ab511af46d0372fc0116c43eb9a38b1b329b72d6d5ab1c
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