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:
- 52bc75cff8f6b7f4e27c0fd7d9132b6290cf9b8617b9ebb7c1c68b4e47f464a3
- Size of remote file:
- 389 kB
- SHA256:
- caaf4a5a920fe1c19b4170b7fe71634d36375a1b666da616cda33140ecdd5bda
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