Instructions to use davaa33/albert-mns-tokenizer-normalized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davaa33/albert-mns-tokenizer-normalized with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("davaa33/albert-mns-tokenizer-normalized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from davaa33/albert-mns-tokenizer-normalized: direct link, hf CLI and curl.
- Browser
- Download file 477 kB
-
https://huggingface.co/davaa33/albert-mns-tokenizer-normalized/resolve/main/spiece.model
- Command line
-
hf download hf://davaa33/albert-mns-tokenizer-normalized/spiece.model
-
curl -L -o spiece.model https://huggingface.co/davaa33/albert-mns-tokenizer-normalized/resolve/main/spiece.model
477 kB
- Xet hash:
- 2c705964bd8c4370634b1bb9f21888282eae132a281b3312f26fdf89f0906261
- Size of remote file:
- 477 kB
- SHA256:
- fa153c6aeaae735faa045e7d2c0195a3cfdd48895b70704acaa0114506f79091
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