Instructions to use certainstar/Trained-Chinese-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use certainstar/Trained-Chinese-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="certainstar/Trained-Chinese-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("certainstar/Trained-Chinese-classification") model = AutoModelForSequenceClassification.from_pretrained("certainstar/Trained-Chinese-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from certainstar/Trained-Chinese-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/certainstar/Trained-Chinese-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://certainstar/Trained-Chinese-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/certainstar/Trained-Chinese-classification/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- e2e5c9447213116e566000625630fdc82c6d5fa1e7d9d522a307beee159d39d0
- Size of remote file:
- 5.05 kB
- SHA256:
- f3717b04d45a79d28ef26b65f930331ef5726e873ced31526c15d7d560fc5c42
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