Instructions to use mykor/fnet-base-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mykor/fnet-base-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mykor/fnet-base-ko")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mykor/fnet-base-ko") model = AutoModelForMaskedLM.from_pretrained("mykor/fnet-base-ko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (d1cb8f0459a93482a5eaf713e8f9b3122d2418c4)3377a26 -
Create README.md
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Update config.json
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Upload tokenizer
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Upload FNetForMaskedLM
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initial commit
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