Instructions to use terhdavid/test-train-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use terhdavid/test-train-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="terhdavid/test-train-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("terhdavid/test-train-model") model = AutoModelForTokenClassification.from_pretrained("terhdavid/test-train-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20807566d022732406112baf9f6ff972beee5403b818f1ab59cb449b8be6eed7
- Size of remote file:
- 4.03 kB
- SHA256:
- 3aa50117e4f7d4347bfc44e1c1a790a83f1647ddf1d0b83b1d878fcdfffb443c
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