Instructions to use junzai/bert_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junzai/bert_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="junzai/bert_test")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junzai/bert_test") model = AutoModelForMaskedLM.from_pretrained("junzai/bert_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from junzai/bert_test: direct link, hf CLI and curl.
- Browser
- Download file 1.2 kB
-
https://huggingface.co/junzai/bert_test/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://junzai/bert_test@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/junzai/bert_test/resolve/refs%2Fpr%2F1/training_args.bin
1.2 kB
- Xet hash:
- af666d314eb234aa15143b76f53a93545fd3bd514c44425af1afdc35469d6aa7
- Size of remote file:
- 1.2 kB
- SHA256:
- 4dc54071a2efef93c309546e79f33393cdc00c8f7617776ff4de07652f067c26
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