Instructions to use btk-mufi/bert-pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use btk-mufi/bert-pretrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="btk-mufi/bert-pretrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("btk-mufi/bert-pretrain") model = AutoModelForMaskedLM.from_pretrained("btk-mufi/bert-pretrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from btk-mufi/bert-pretrain: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/btk-mufi/bert-pretrain/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://btk-mufi/bert-pretrain/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/btk-mufi/bert-pretrain/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- b0cbd905f2df1119f538f59b43c6ec946c624bdb28ca4fa2b7877661e57743e4
- Size of remote file:
- 433 MB
- SHA256:
- 6826115f4fcf9c2cb93acc56933273821b028ee42cb68fc594360e3559012e71
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