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:
- 07d488ba6256fd59b95bad62043f06bf27f482f10dc2547c3222b90cf2261431
- Size of remote file:
- 321 kB
- SHA256:
- 9dd7f9ae7bc7c32e8e7fd6c079fc741a46d1a261a6ed000d06d08d421ba51c7c
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