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:
- b05920812106fd04c4a06f44ffdd66f11f351b2318a7e437084690721cc16905
- Size of remote file:
- 181 kB
- SHA256:
- 996592a55c51e71de4d9398e70c37107649a623611e40f5d5b9b3980d51dce77
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