Instructions to use BeitTigreAI/tigre-spm-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BeitTigreAI/tigre-spm-tokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BeitTigreAI/tigre-spm-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from BeitTigreAI/tigre-spm-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 585 kB
-
https://huggingface.co/BeitTigreAI/tigre-spm-tokenizer/resolve/main/tokenizer.model
- Command line
-
hf download hf://BeitTigreAI/tigre-spm-tokenizer/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/BeitTigreAI/tigre-spm-tokenizer/resolve/main/tokenizer.model
585 kB
- Xet hash:
- f89caf1d2f9ce8b5c20caeb7d7f5cb89fde35350827766cd31edd3e17bb5f328
- Size of remote file:
- 585 kB
- SHA256:
- ac957dd646721c422a88627cc0d1aec3a91d68f9a3843ecd5117be3f918cc1a2
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