Instructions to use hf-tiny-model-private/tiny-random-ErnieMForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ErnieMForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-ErnieMForTokenClassification")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-ErnieMForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 753ab3e3cc95e00a492d502d73e410e5d288964d26da97bb3911ff168a096f67
- Size of remote file:
- 32.2 MB
- SHA256:
- b2fb9a9e18216df38664c915bcb5264c511a66fa89ac24f411e10192b58829aa
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