Instructions to use Raven47/bert_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raven47/bert_finetune with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Raven47/bert_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download label_encoder.joblib from Raven47/bert_finetune: direct link, hf CLI and curl.
- Browser
- Download file 596 Bytes
-
https://huggingface.co/Raven47/bert_finetune/resolve/main/label_encoder.joblib
- Command line
-
hf download hf://Raven47/bert_finetune/label_encoder.joblib
-
curl -L -o label_encoder.joblib https://huggingface.co/Raven47/bert_finetune/resolve/main/label_encoder.joblib
596 Bytes
- Xet hash:
- ac35fc4b2cfe992a16eb05678c0bcf4abf760b67b2393c92ba2ff5fccc482dd5
- Size of remote file:
- 596 Bytes
- SHA256:
- d7449fa0646f510621b86745174133cd758b3c2877123b074d7564cbf687582d
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