Instructions to use hf-internal-testing/tiny-random-MptForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MptForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MptForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MptForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MptForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24c0e0b92e244821be99f4d624e938fe98bfde0e0f7ab099755bf49e0ad1b1f0
- Size of remote file:
- 382 kB
- SHA256:
- 83e1f88f818737810522180c9fa378de385cbcb6b27c840e8e20736187d7523b
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