Instructions to use hf-internal-testing/tiny-random-XLNetForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XLNetForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-XLNetForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XLNetForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-XLNetForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
Upload tiny models for XLNetForSequenceClassification
Browse files- pytorch_model.bin +1 -1
- tf_model.h5 +1 -1
pytorch_model.bin
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tf_model.h5
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