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 pytorch_model.bin from erica/kcbase400: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/erica/kcbase400/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://erica/kcbase400/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/erica/kcbase400/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- ee020bc1af0dee7688a4980a7365cbd4dcc3a217ba4625b8dcdccfd4568c0cd5
- Size of remote file:
- 436 MB
- SHA256:
- f6058ced390d839b9b3d46e57085d147283f7c9d2cc1cd740e89f32cca0e63b9
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