Instructions to use junzai/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junzai/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="junzai/bert_finetuning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("junzai/bert_finetuning_test") model = AutoModelForSequenceClassification.from_pretrained("junzai/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from junzai/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 920 Bytes
-
https://huggingface.co/junzai/bert_finetuning_test/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://junzai/bert_finetuning_test@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/junzai/bert_finetuning_test/resolve/refs%2Fpr%2F1/training_args.bin
920 Bytes
- Xet hash:
- 4d45751a8f074695b56cdae2c94fad7d79033b0355fe6137b318c69c386205cb
- Size of remote file:
- 920 Bytes
- SHA256:
- 08736ff4c5b868e4ecbe8750f9780c8ef1f820336c77d5620641bc5eddb34450
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