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:
- c232e97dde14f96a0733016ab25444be917b8d171d182ed0d8f8aea5e95c2b8c
- Size of remote file:
- 389 kB
- SHA256:
- c0f9479fe907f3938944f3a7b7b79d94709749e1ae9f2a911740e532036b1830
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