Instructions to use Galvin/my_ebm_model_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Galvin/my_ebm_model_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Galvin/my_ebm_model_test")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Galvin/my_ebm_model_test") model = AutoModelForTokenClassification.from_pretrained("Galvin/my_ebm_model_test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b19c340f37efa9bb6881ea630019f53cb7e773f6b1f2202a8326f5dc79d4cac5
- Size of remote file:
- 3.58 kB
- SHA256:
- b714103cbd42594d9124242209c157ee13bf64d3f32d5f9001281c288f508e46
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