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:
- 4752018cb40182356d8ac7400716349ed44bd56836701abf5be7543e1d372330
- Size of remote file:
- 233 kB
- SHA256:
- 0c6fae8cf725fc1d311011f98526851d7ca583f69f8b38c4c2dcdd4c8690f7ea
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