Instructions to use hf-tiny-model-private/tiny-random-ErnieMForSequenceClassification 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-ErnieMForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-ErnieMForSequenceClassification")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-ErnieMForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c360cfdf5c10d85ad91ec94fabefc866e45bc248e33d873f4f60b3e4d9266f05
- Size of remote file:
- 32.2 MB
- SHA256:
- f6800c95169e7da305304c48186452d3ce3fcbc2e8904cb79fbb9c0cd545cd7b
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