Instructions to use TransWiC/xlmr-large-zh-CLS-BT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/xlmr-large-zh-CLS-BT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/xlmr-large-zh-CLS-BT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/xlmr-large-zh-CLS-BT") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/xlmr-large-zh-CLS-BT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TransWiC/xlmr-large-zh-CLS-BT: direct link, hf CLI and curl.
- Browser
- Download file 2.28 GB
-
https://huggingface.co/TransWiC/xlmr-large-zh-CLS-BT/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://TransWiC/xlmr-large-zh-CLS-BT@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TransWiC/xlmr-large-zh-CLS-BT/resolve/refs%2Fpr%2F1/pytorch_model.bin
2.28 GB
- Xet hash:
- 63d17b6f0a99ffe6643996db4c03226de594bf9843471e0452aa34ce639ed3c1
- Size of remote file:
- 2.28 GB
- SHA256:
- 4686aba7ffb2be9fd00e4bbf2aca91107c1dc612c16d53908b6f5fefdf2c5216
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