Instructions to use hf-internal-testing/tiny-random-YosoForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-YosoForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-YosoForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-YosoForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-YosoForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b74a61159e6c1a7870ec1aa85662385cf1989a9b4ce228c07392d74d4014b34
- Size of remote file:
- 372 kB
- SHA256:
- b18a6a1d4b7609c43ac8c20a56325ea55183775524d3fb12f0c9ecd0dbf52dd2
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