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:
- ac56a672b691c78428c1b68ffb5abe3c1fe210d32cb1ca3ab959dfba50d3734d
- Size of remote file:
- 181 kB
- SHA256:
- 88f40519c3c8a3078285fd2e73cd8b67b0ceb8f0c14a38e0fcadec63206a7f8f
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