Instructions to use hw2942/bert-base-chinese-climate-related-prediction-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hw2942/bert-base-chinese-climate-related-prediction-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hw2942/bert-base-chinese-climate-related-prediction-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hw2942/bert-base-chinese-climate-related-prediction-3") model = AutoModelForSequenceClassification.from_pretrained("hw2942/bert-base-chinese-climate-related-prediction-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a83f54d578a31f58deefe926bdf695011b5e131ff64c556f7452b9c9e4951998
- Size of remote file:
- 409 MB
- SHA256:
- 7f17187342067ca2d7747355c976426ad22eaedb984055e1c6d13676a18981c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.