Instructions to use lian01110/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lian01110/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lian01110/bert_finetuning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lian01110/bert_finetuning_test") model = AutoModelForMaskedLM.from_pretrained("lian01110/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lian01110/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/lian01110/bert_finetuning_test/resolve/main/training_args.bin
- Command line
-
hf download hf://lian01110/bert_finetuning_test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lian01110/bert_finetuning_test/resolve/main/training_args.bin
1.21 kB
- Xet hash:
- bfb34143c3e0c2304d3b1e564d2959ced23a3636dfa2610dbb6d82474a19dec9
- Size of remote file:
- 1.21 kB
- SHA256:
- 30dda970c2d049d35583aac0e85bfe3938c0e441ad24bad4bc10ef9c3ff193fa
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