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:
- c411f6f5034d45be933f1bec59106ee0bf7fad38cd7b59d4023386c4712731dd
- Size of remote file:
- 321 kB
- SHA256:
- 82b53ac985da5e9165ad673bc744e74242758613423e8e7260f29b6e25463258
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