Instructions to use BigSalmon/Rowerta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/Rowerta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigSalmon/Rowerta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/Rowerta") model = AutoModelForMaskedLM.from_pretrained("BigSalmon/Rowerta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigSalmon/Rowerta: direct link, hf CLI and curl.
- Browser
- Download file 2.48 kB
-
https://huggingface.co/BigSalmon/Rowerta/resolve/main/training_args.bin
- Command line
-
hf download hf://BigSalmon/Rowerta/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigSalmon/Rowerta/resolve/main/training_args.bin
2.48 kB
- Xet hash:
- 86a6dfc3ca32128f98736240d7b645c771551a54c474d6b6aa07be36f1302a07
- Size of remote file:
- 2.48 kB
- SHA256:
- e82f6fa4bce997e1ec35bac204ee3d06b5cced4b1764ff2b0a5f95725f00b1c3
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