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:
- 54c2e61af35d71b33ee1c0be9286ef8b0b3a7a154758f431ed2b6693de5b074a
- Size of remote file:
- 389 kB
- SHA256:
- 1fbaf57276775898beaad48a94f6a75a42f491e977307d2faffd80b42aa1cd9f
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