Instructions to use YanJiangJerry/task2_xlnet-large-cased_3_4_2e-05_0.01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YanJiangJerry/task2_xlnet-large-cased_3_4_2e-05_0.01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YanJiangJerry/task2_xlnet-large-cased_3_4_2e-05_0.01")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YanJiangJerry/task2_xlnet-large-cased_3_4_2e-05_0.01") model = AutoModelForSequenceClassification.from_pretrained("YanJiangJerry/task2_xlnet-large-cased_3_4_2e-05_0.01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c8e688feb6fd03ca59ef821a6716cd8a209d53bb8019cffce8525893e3c9d05
- Size of remote file:
- 4.03 kB
- SHA256:
- ab1818c4ffcc151be8b37b386b1b067352faa62a153551c42f5f1b5251d270d8
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