Instructions to use adriansyahdr/adrBert-base-p1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adriansyahdr/adrBert-base-p1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="adriansyahdr/adrBert-base-p1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("adriansyahdr/adrBert-base-p1") model = AutoModelForMaskedLM.from_pretrained("adriansyahdr/adrBert-base-p1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from adriansyahdr/adrBert-base-p1: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/adriansyahdr/adrBert-base-p1/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://adriansyahdr/adrBert-base-p1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/adriansyahdr/adrBert-base-p1/resolve/main/flax_model.msgpack
504 MB
- Xet hash:
- c5edaed027e589f87f5f370d0bb7772309c08cf845dc0b5ec61d10351f7e4b6e
- Size of remote file:
- 504 MB
- SHA256:
- 5b28e33e9e9ea70a8cdb80b52eee52799ce28d599c1f97162de4935e7082d658
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