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:
- a66e180b339287c8182f18fbd86f03844db9a296bc29b151891c18028a4e07a7
- Size of remote file:
- 233 kB
- SHA256:
- 4893e37c8df02f2ae7a7fe6d9718fb6ae67db30cadf34f9b6078820d2dbf8f82
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