Instructions to use davaa33/mns_tokenizer_normalized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davaa33/mns_tokenizer_normalized with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("davaa33/mns_tokenizer_normalized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from davaa33/mns_tokenizer_normalized: direct link, hf CLI and curl.
- Browser
- Download file 478 kB
-
https://huggingface.co/davaa33/mns_tokenizer_normalized/resolve/main/spiece.model
- Command line
-
hf download hf://davaa33/mns_tokenizer_normalized/spiece.model
-
curl -L -o spiece.model https://huggingface.co/davaa33/mns_tokenizer_normalized/resolve/main/spiece.model
478 kB
- Xet hash:
- 183b04bc7d1d19fa12577f38885efda92d4025de115e6d059784a87f89a333cc
- Size of remote file:
- 478 kB
- SHA256:
- 0c4c4de674e45ec7225358bce8cd211d2ce300f504e382c48f9cbca4f940d959
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