Instructions to use BigSalmon/FormalRobertaa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/FormalRobertaa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigSalmon/FormalRobertaa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/FormalRobertaa") model = AutoModelForMaskedLM.from_pretrained("BigSalmon/FormalRobertaa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigSalmon/FormalRobertaa: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/BigSalmon/FormalRobertaa/resolve/main/training_args.bin
- Command line
-
hf download hf://BigSalmon/FormalRobertaa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigSalmon/FormalRobertaa/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 0e99cf102f93cc2adb0aad7e5433bbf464df99fe00e5ddab0638b1d2d0d65402
- Size of remote file:
- 2.86 kB
- SHA256:
- cc9c499ea867c5ffae62f74d01453b2bb0ef19b42ddf6ca6351aac760a08c3ef
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