Instructions to use activebus/BERT-PT_rest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use activebus/BERT-PT_rest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="activebus/BERT-PT_rest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("activebus/BERT-PT_rest") model = AutoModelForMaskedLM.from_pretrained("activebus/BERT-PT_rest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from activebus/BERT-PT_rest: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/activebus/BERT-PT_rest/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://activebus/BERT-PT_rest/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/activebus/BERT-PT_rest/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- a05eb9303df90a78e0f998a21788a76af5f516987e25578bfcdfda0c219e1015
- Size of remote file:
- 438 MB
- SHA256:
- 610a1e030b00c77e55021185f73ed8ad64cfb16e8e50dfdf242ce4aa523291c9
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