Instructions to use hf-internal-testing/tiny-random-FalconForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FalconForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-FalconForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FalconForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-FalconForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad9c9f0914e75d3786413b6514d183a3a4e7b45127f96902c78bb8252b7ff844
- Size of remote file:
- 233 kB
- SHA256:
- 4c38602019d9708f91ac2c73fc370aae27f39b22df6e7c0930fbe696bc84fbe1
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