Instructions to use hf-tiny-model-private/tiny-random-GPT2ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-GPT2ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-GPT2ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPT2ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-GPT2ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 541a39e3228843037b120c079ecbdd8d05f4d453c87fcbcda5f33da23281117f
- Size of remote file:
- 1.65 MB
- SHA256:
- 5387852328bf58d6e7ac5a5700623df7fac4a3f19efb0922874b2ce1a3d0a7a2
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