Instructions to use textattack/xlnet-base-cased-SST-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/xlnet-base-cased-SST-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/xlnet-base-cased-SST-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/xlnet-base-cased-SST-2") model = AutoModelForSequenceClassification.from_pretrained("textattack/xlnet-base-cased-SST-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e600d5b65070c371c373ee4f8608ebaae96202853a8a19080a7e3c35e06653aa
- Size of remote file:
- 1.05 kB
- SHA256:
- 2b7f89f2ee6fff00d3f65e0340fa9500f5f3947b9fa7e3aea3e38cd306c49194
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.