Instructions to use Jethuestad/distilbert-base-uncased-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jethuestad/distilbert-base-uncased-test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jethuestad/distilbert-base-uncased-test2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jethuestad/distilbert-base-uncased-test2") model = AutoModelForTokenClassification.from_pretrained("Jethuestad/distilbert-base-uncased-test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a995661b9b2003421c7fb08ec421fc9e735df9d604821245a80ef87b30629fcb
- Size of remote file:
- 3.31 kB
- SHA256:
- 9199adb81dcb0ab6fb4adf93457778b2e4b1f60b5a221d9c63927aaba1c24345
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