Instructions to use Serialtechlab/llama-3.1-8b-dhivehi-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Serialtechlab/llama-3.1-8b-dhivehi-tokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Serialtechlab/llama-3.1-8b-dhivehi-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Serialtechlab/llama-3.1-8b-dhivehi-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/Serialtechlab/llama-3.1-8b-dhivehi-tokenizer/resolve/main/tokenizer.json
- Command line
-
hf download hf://Serialtechlab/llama-3.1-8b-dhivehi-tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Serialtechlab/llama-3.1-8b-dhivehi-tokenizer/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 4bef95ce21ae563b5a12116397a91b7fe1a9af7e3a9ae3b8cfc3cdde2e9e6a6c
- Size of remote file:
- 17.2 MB
- SHA256:
- da99bdca90194a7cec2b22acccf6b857e78703fd836d81b806929f828f8f1933
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