Instructions to use hf-internal-testing/tiny-random-GPT2ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPT2ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-GPT2ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-GPT2ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de15f5fa02cd20a934a82ef225625dc2b7d8dfe190ed4d4b1e6fc633d35d9d95
- Size of remote file:
- 1.65 MB
- SHA256:
- e624e4ad06c273b5b5d6d476c0cc6517e7554ba9f6994f85c7679bec7300d62b
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