Instructions to use BigSalmon/FormalBerta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/FormalBerta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigSalmon/FormalBerta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/FormalBerta") model = AutoModelForMaskedLM.from_pretrained("BigSalmon/FormalBerta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BigSalmon/FormalBerta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/BigSalmon/FormalBerta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BigSalmon/FormalBerta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BigSalmon/FormalBerta/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- f072a7ce41eec081ca27866cff0bd9d1479c077b9afcd0c46d12ee40a4b7fb29
- Size of remote file:
- 499 MB
- SHA256:
- 4dd7f2f2d3746b84447ec4d0f6fc48a44287e9a6e4009d04cf57072766cc9378
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