Transformers
tokenizer
bpe
byte-level-bpe
multilingual
code
python
latex
small-language-models
embedding-efficiency
flores-200
tokenizerbench
chat-template
fill-in-the-middle
Instructions to use JamesQuartz/QT-VII-Tokenizer-Family with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JamesQuartz/QT-VII-Tokenizer-Family with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JamesQuartz/QT-VII-Tokenizer-Family", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download benchmark_charts/3_FLORES_Regional_Scripts_Comparison.png from JamesQuartz/QT-VII-Tokenizer-Family: direct link, hf CLI and curl.
- Browser
- Download file 361 kB
-
https://huggingface.co/JamesQuartz/QT-VII-Tokenizer-Family/resolve/main/benchmark_charts/3_FLORES_Regional_Scripts_Comparison.png
- Command line
-
hf download hf://JamesQuartz/QT-VII-Tokenizer-Family/benchmark_charts/3_FLORES_Regional_Scripts_Comparison.png
-
curl -L -o 3_FLORES_Regional_Scripts_Comparison.png https://huggingface.co/JamesQuartz/QT-VII-Tokenizer-Family/resolve/main/benchmark_charts/3_FLORES_Regional_Scripts_Comparison.png
361 kB

- Xet hash:
- 3af62b9ca1245dfeba2d3c74dcdd54d3e4bbbdbb734bdaeab433b6625abf33fd
- Size of remote file:
- 361 kB
- SHA256:
- a71fd99a200835efd9d240668fb7be9f0c3128e0f0e730a92d5f685d32701205
·
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