Instructions to use erica/kob400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erica/kob400 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="erica/kob400")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("erica/kob400") model = AutoModelForMaskedLM.from_pretrained("erica/kob400", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from erica/kob400: direct link, hf CLI and curl.
- Browser
- Download file 369 MB
-
https://huggingface.co/erica/kob400/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://erica/kob400/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/erica/kob400/resolve/main/flax_model.msgpack
369 MB
- Xet hash:
- a7950eb36978688019131a39124d8a09db26f096c179acdd1c9be2928b0aae53
- Size of remote file:
- 369 MB
- SHA256:
- b014ead6e9f261331636af8bfd40c89e6f768b85fa3335792ccb1ff95ea6a6e5
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