Instructions to use hf-tiny-model-private/tiny-random-FunnelForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FunnelForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-FunnelForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 251390517abdcef3cb1fde47dc94b7afad07c71809af56e5d78fa602f07ce2e1
- Size of remote file:
- 315 kB
- SHA256:
- 4d7762b0ca6c55ed446b50361bed03a3fd3eaa1070a595143d90210d41b8d2e4
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