Instructions to use Stepa/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Stepa/my_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Stepa/my_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Stepa/my_model") model = AutoModelForTokenClassification.from_pretrained("Stepa/my_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25578c1647e455a8cfe297f8d5a16fd9bcf2715b1b4f7895a59595a2411d0aa3
- Size of remote file:
- 1.7 GB
- SHA256:
- edf4cc97546f05931884f59c1d9fb31b9469cfc93e10ab5a8eb943b181987296
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