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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4de203acdfea537bef37cec49a4bddd6d917ecf1511c31032fbf77f07aa75dcc
- Size of remote file:
- 382 kB
- SHA256:
- a0b566380828d27563dc6ee7c6dc2a945d49ddd0b47524e73808ee92c362ddda
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