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:
- 823061e58868fafa1930ee75d0092017c82e9a1cd678da05c7d2117dafc31ba6
- Size of remote file:
- 1.6 MB
- SHA256:
- fb677f0398d5e95ad6c48b786168bc0f4b762d59dd6f8f9f61b2dacc460a5a0c
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