Fix Tokenizer bug(space not applied when decoding) after
transforemrs>=4.34.0
Llama-2-Ko
🦙🇰🇷
Llama-2-Ko serves as an advanced iteration of Llama 2, benefiting from an expanded vocabulary and the inclusion of a Korean corpus in its further pretraining. Just like its predecessor, Llama-2-Ko operates within the broad range of generative text models that stretch from 7 billion to 70 billion parameters. This repository focuses on the 7B pretrained version, which is tailored to fit the Hugging Face Transformers format. For access to the other models, feel free to consult the index provided below.
Model Details
Model Developers
Junbum Lee (Beomi)
Variations
Llama-2-Ko will come in a range of parameter sizes — 7B, 13B, and 70B — as well as pretrained and fine-tuned variations.
Input
Models input text only.
Output
Models generate text only.
Model Architecture
Llama-2-Ko is an auto-regressive language model that uses an optimized transformer architecture based on Llama-2.
Since Llama-2-Ko uses FastTokenizer provided by HF tokenizers NOT sentencepiece package,
it is required to use
use_fast=True
option when initialize tokenizer.
Apple Sillicon does not support BF16 computing, use CPU instead. (BF16 is supported when using NVIDIA GPU)
Citation
@misc {l._junbum_2023,
author = { {L. Junbum} },
title = { llama-2-ko-7b (Revision 4a9993e) },
year = 2023,
url = { https://huggingface.co/beomi/llama-2-ko-7b },
doi = { 10.57967/hf/1098 },
publisher = { Hugging Face }
}
More Information About llama-2-ko-7b huggingface.co Model
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