Instructions to use hizella/aBERT_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hizella/aBERT_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hizella/aBERT_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hizella/aBERT_test") model = AutoModelForMaskedLM.from_pretrained("hizella/aBERT_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hizella/aBERT_test: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/hizella/aBERT_test/resolve/main/training_args.bin
- Command line
-
hf download hf://hizella/aBERT_test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hizella/aBERT_test/resolve/main/training_args.bin
2.8 kB
- Xet hash:
- 9b75b706b66ead07694afadecc090a52317a597c957ac55bb8bbde03d03ea8a8
- Size of remote file:
- 2.8 kB
- SHA256:
- e74d494bb0d03f53b17fe3db4bb1a504ab726e3733a21b31e815b480f66ae8d2
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