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 optimizer.pt from hizella/aBERT_test: direct link, hf CLI and curl.
- Browser
- Download file 89.8 MB
-
https://huggingface.co/hizella/aBERT_test/resolve/main/optimizer.pt
- Command line
-
hf download hf://hizella/aBERT_test/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/hizella/aBERT_test/resolve/main/optimizer.pt
89.8 MB
- Xet hash:
- d86fa45b842ac31a0dd3c9ea1ce72c3aa733f0b4631869df07bcdaece1ae9ea5
- Size of remote file:
- 89.8 MB
- SHA256:
- ef44f509b6612b43998c7c56afbd987ddef5c066e278397d3db447a88ba99c1d
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