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:
- eb0ccaa4c58ee354fab73c797ffc5ef8101103463a9087ef14a129714e093102
- Size of remote file:
- 8.97 MB
- SHA256:
- e5fadd26e65fbcb29bdff15b116e99d941003aeba6cc5f1742ba141fa2735e41
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