Instructions to use adriansyahdr/adrBert-base-p2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adriansyahdr/adrBert-base-p2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("adriansyahdr/adrBert-base-p2") model = AutoModelForPreTraining.from_pretrained("adriansyahdr/adrBert-base-p2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from adriansyahdr/adrBert-base-p2: direct link, hf CLI and curl.
- Browser
- Download file 506 MB
-
https://huggingface.co/adriansyahdr/adrBert-base-p2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://adriansyahdr/adrBert-base-p2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/adriansyahdr/adrBert-base-p2/resolve/main/flax_model.msgpack
506 MB
- Xet hash:
- cb69deb475c6cd1e5ef7442f2a66b3c091e082d92ee897b1333583471df52112
- Size of remote file:
- 506 MB
- SHA256:
- 47b90bcbab90591276f0d9d11ad0bd26c4665480612f651d451c086158e1197e
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