Instructions to use hf-internal-testing/tiny-random-MPNetForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MPNetForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MPNetForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MPNetForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MPNetForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fc22792523bd9f5f7166cf5e01cd66efb47b6e0eea0dbef59e50059ad37114d
- Size of remote file:
- 955 kB
- SHA256:
- f603d20b3fd275b00715368ff944c3a53cfeafbf19acbe08b2e08eeaeaa10d78
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