README.md

---
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-Q4_K_M-GGUF
This model was converted to GGUF format from [`utrobinmv/t5_translate_en_ru_zh_large_1024_v2`](https://huggingface.co/utrobinmv/t5_translate_en_ru_zh_large_1024_v2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/utrobinmv/t5_translate_en_ru_zh_large_1024_v2) for more details on the model.

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

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q4_K_M-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q4_K_M-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q4_k_m.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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-Q4_K_M-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo KeyserSoze1/t5_translate_en_ru_zh_large_1024_v2-Q4_K_M-GGUF --hf-file t5_translate_en_ru_zh_large_1024_v2-q4_k_m.gguf -c 2048
```