Instructions to use hf-internal-testing/tiny-random-FlaubertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FlaubertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-FlaubertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FlaubertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-FlaubertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20c197f53a69ee5601583b56dd93a502db0376f820259fb1b6cc773cdf43b43f
- Size of remote file:
- 9.07 MB
- SHA256:
- cd1502cddf5f0c56315e3d77b2e26afe81910d5c47adc6d9d94d77a239bf235a
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