metadata

base_model: utrobinmv/t5_translate_en_ru_zh_large_1024_v2
datasets:
  - ccmatrix
language:
  - ru
  - zh
  - en
license: apache-2.0
metrics:
  - sacrebleu
tags:
  - translation
  - llama-cpp
  - gguf-my-repo
widget:
  - example_title: translate zh-ru
    text: |
      translate to ru: 开发的目的是为用户提供个人同步翻译。
  - example_title: translate ru-en
    text: >
      translate to en: Цель разработки — предоставить пользователям личного
      синхронного переводчика.
  - example_title: translate en-ru
    text: >
      translate to ru: The purpose of the development is to provide users with a
      personal synchronized interpreter.
  - example_title: translate en-zh
    text: >
      translate to zh: The purpose of the development is to provide users with a
      personal synchronized interpreter.
  - example_title: translate zh-en
    text: |
      translate to en: 开发的目的是为用户提供个人同步解释器。
  - example_title: translate ru-zh
    text: >-
      translate to zh: Цель разработки — предоставить пользователям личного
      синхронного переводчика.

KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q8_0-GGUF

This model was converted to GGUF format from utrobinmv/t5_translate_en_ru_zh_large_1024_v2 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q8_0-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q8_0-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q8_0-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q8_0.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q8_0-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q8_0.gguf -c 2048