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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a6d8569abe6f7ee10c3c5001fd7ef3c51efe415bb01de3c2cabe62417b6624a
- Size of remote file:
- 321 kB
- SHA256:
- aeb2615b9457e1b96b5dc14134f1ad27fe4ddbf70c1c3db939979ce5ca764ec8
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