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:
- 442c7877ef2d44506d5432cdbba4d0a78b2683b36dbb09f2d53c878164f00d67
- Size of remote file:
- 389 kB
- SHA256:
- 15969872c739bb2ba26a12d461b7d13359141fdaea267b41b8d639b29272ae25
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