Instructions to use erica/kcbase400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erica/kcbase400 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="erica/kcbase400")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("erica/kcbase400") model = AutoModelForMaskedLM.from_pretrained("erica/kcbase400", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from erica/kcbase400: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/erica/kcbase400/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://erica/kcbase400/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/erica/kcbase400/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- 28cbcbd6ba2990ab04a4798e8db93c9eda490a15c8c3c73cc4b8f5849f9abaa8
- Size of remote file:
- 436 MB
- SHA256:
- 69302522c22dcfb4e8f5c394d280a8bcc94b7aae6514f71d39da5c236c75fda7
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