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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a7cc3c0b13369d5fed4e201e106d284a8317aebe7695e1d63a6168e4db10804
- Size of remote file:
- 1.6 MB
- SHA256:
- 2f07a7eb9ce3198eedf2ea2dfa3528342301d9b9e9e65426ebec8a06b066c9f5
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