Instructions to use hf-internal-testing/tiny-random-MvpForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MvpForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MvpForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MvpForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MvpForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a2483ef18dbbcf0cba0d92215d389703a5c7ed007f4461da57c1704d8ed7060
- Size of remote file:
- 140 kB
- SHA256:
- d1814105c39780a341f4a19ff83e81f82afd060b50b6023d1f8d58f98fb7db8f
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