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:
- 054a80126bb1e85b0bcd1c87daf1f778e530a2c4f0cca59732ba670f60bb06e6
- Size of remote file:
- 321 kB
- SHA256:
- 45b320cdaa99ca9bb9f1930626ba9cd772aafee345a102c5cf1c55612e9e1723
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