Instructions to use hf-internal-testing/tiny-random-GPTNeoXForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoXForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-GPTNeoXForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b808d28acfa1e5e56d7e3b4717682e605c95139213c4eafcd2efd7dc9f55908
- Size of remote file:
- 1.59 MB
- SHA256:
- d1c9f3103bc1547d705a127ac39f3537fd4e1eca37e6dedd3257f6ac5be274f7
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