Instructions to use BigSalmon/Flowberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/Flowberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigSalmon/Flowberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/Flowberta") model = AutoModelForMaskedLM.from_pretrained("BigSalmon/Flowberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigSalmon/Flowberta: direct link, hf CLI and curl.
- Browser
- Download file 2.48 kB
-
https://huggingface.co/BigSalmon/Flowberta/resolve/main/training_args.bin
- Command line
-
hf download hf://BigSalmon/Flowberta/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigSalmon/Flowberta/resolve/main/training_args.bin
2.48 kB
- Xet hash:
- d21146d92fa1c14b4ea79c716a4142546308bff2d2e646d0c823fbf1e9851486
- Size of remote file:
- 2.48 kB
- SHA256:
- 51dae89a5c58b0806210589d680261d77fbdce2ca874990e44d6b70179facb77
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