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:
- 2f82fe9e510ea6b45023bd6dc723e81afd5058e04173065e49fc34495d256ebf
- Size of remote file:
- 233 kB
- SHA256:
- c96f39812091927a891028aa7dae8e2c1a62ae7e9dcfae718ce20f28ff5d385b
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