Instructions to use beyhan/checkpoint-3750 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beyhan/checkpoint-3750 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="beyhan/checkpoint-3750")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("beyhan/checkpoint-3750") model = AutoModelForTokenClassification.from_pretrained("beyhan/checkpoint-3750") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8e4d348088643fc2102b3ab91a043fbabe6c6271ef4d2f487306edb73415be0
- Size of remote file:
- 440 MB
- SHA256:
- b9580469c1e6d6d81b65303a2885dfcca856ea42e8bc2c6dc5bece635e4484bf
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