Instructions to use hf-internal-testing/tiny-random-GPTNeoForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-GPTNeoForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76fbf5717c19ecfb2639eae359ce6ab9a755ce76f2445601538523e6ef25df2a
- Size of remote file:
- 1.45 MB
- SHA256:
- 32074c759f6508a296c0d02d1bd6e2ee3a603075cd08d17a10bf8b979be2aaae
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