Instructions to use hf-internal-testing/tiny-random-MptForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MptForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MptForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MptForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MptForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b4f7f6a37de261870817cd23543f77c6dce2f0cc4fb21e4cd4e21ba52354f65
- Size of remote file:
- 389 kB
- SHA256:
- 3ea63d37be494ea62fa45d653bc2a29098987388d21688464dbbfe5b020b3978
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