Instructions to use BigSalmon/FormalBerta2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/FormalBerta2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigSalmon/FormalBerta2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/FormalBerta2") model = AutoModelForMaskedLM.from_pretrained("BigSalmon/FormalBerta2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigSalmon/FormalBerta2: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/BigSalmon/FormalBerta2/resolve/main/training_args.bin
- Command line
-
hf download hf://BigSalmon/FormalBerta2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigSalmon/FormalBerta2/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 4deef64c5e0c5355468ab00291ebe6c78c1b5a4514b91ba512e61f144d411ce2
- Size of remote file:
- 2.86 kB
- SHA256:
- 7ca01cbffaab8a0b1773a2f033767675b072ae7a47d9cdc60db9acbbdeb04be8
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