Instructions to use MagicalCat29/model_save_test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MagicalCat29/model_save_test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MagicalCat29/model_save_test2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MagicalCat29/model_save_test2") model = AutoModelForTokenClassification.from_pretrained("MagicalCat29/model_save_test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6ac64561935b4836fc9ad4bbb1f5402341cb6a0401d2eb6fba55ad959ad8776
- Size of remote file:
- 407 MB
- SHA256:
- e119be24dbf17ad545bed675a877f6de9ef3018a97aebbc8f6944cb9dd761aae
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