Instructions to use hf-internal-testing/tiny-random-Starcoder2ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Starcoder2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-Starcoder2ForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Starcoder2ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-Starcoder2ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61c55bc8efe9c93aa30865aa6c6103fc49a07b65c3e8c721662aee43fcdfb5b8
- Size of remote file:
- 181 kB
- SHA256:
- 4fe8ef24889919228f46f3be9dcc5a827e2d6f53e98f58ec01fa34a2a82951cc
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