Instructions to use schnell/bert-small-ipadic-unigram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use schnell/bert-small-ipadic-unigram with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="schnell/bert-small-ipadic-unigram")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("schnell/bert-small-ipadic-unigram") model = AutoModelForMaskedLM.from_pretrained("schnell/bert-small-ipadic-unigram", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from schnell/bert-small-ipadic-unigram: direct link, hf CLI and curl.
- Browser
- Download file 2.02 MB
-
https://huggingface.co/schnell/bert-small-ipadic-unigram/resolve/main/tokenizer.json
- Command line
-
hf download hf://schnell/bert-small-ipadic-unigram/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/schnell/bert-small-ipadic-unigram/resolve/main/tokenizer.json
2.02 MB
- Xet hash:
- d635507bd8539f9bba4ce1ee0cf4947c7cd4dbb97ec029bdbdeab122d81f94a4
- Size of remote file:
- 2.02 MB
- SHA256:
- 522e963abd859af7d20e174403a6d639af482c17a395587e9d6f0e3aebe64038
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