Instructions to use EstrixDS/XLNet_SemEval_Task1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EstrixDS/XLNet_SemEval_Task1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EstrixDS/XLNet_SemEval_Task1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EstrixDS/XLNet_SemEval_Task1") model = AutoModelForSequenceClassification.from_pretrained("EstrixDS/XLNet_SemEval_Task1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7301133b30af3e7ea2b13eb4e1a7eb6d2769a9fab3ec4fba53f44454607d7ab
- Size of remote file:
- 1.45 GB
- SHA256:
- 7ed8c66229dd4225bf329639f6e83527c1baf41c360cc68a78336fc0b9061c2a
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