Instructions to use hf-internal-testing/tiny-random-GPTBigCodeForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTBigCodeForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-GPTBigCodeForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70782c5acf2aa8187465619906354a642bc7d2971b0c809f6c29792c946f261d
- Size of remote file:
- 307 kB
- SHA256:
- 9747b8090d5a757833b5f3ee3a3ae9d7fbc3208820cb5812f7ceced722acf73e
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