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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c032ff78e3ba6c07e5021bb4827dca0914704a606ca045bfdbf85220c434ef1c
- Size of remote file:
- 1.47 MB
- SHA256:
- 69eaf91d93bbdee0e0c7912dcbfd5d612087ac41c7ffe003e245d785401e63f0
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