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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97853cfe5c24e7d970f85506dc156629dbc6e835b6b5a04ee2a91a882f7b0de4
- Size of remote file:
- 389 kB
- SHA256:
- d6ebac52d0b4954db1d7ee71b84f27058925f836c075fea8e83ddaf417e8b1c8
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