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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5676da02fb9baa4113f2b066ed72f040d8060a20d94f5401daea09cb1231c689
- Size of remote file:
- 785 kB
- SHA256:
- f3d8dbf50938e4d2c02e4989f9ccc2e439c7e0529857e3769c647700c6eef4cb
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