---
base_model: Krystalan/DRT-8B
language:
- en
- zh
license: cc-by-nc-sa-4.0
pipeline_tag: text-generation
tags:
- machine tranlsation
- O1-like model
- Chat
- llama-cpp
- gguf-my-repo
---

# Triangle104/DRT-8B-Q4_K_S-GGUF
This model was converted to GGUF format from [`Krystalan/DRT-8B`](https://huggingface.co/Krystalan/DRT-8B) 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/Krystalan/DRT-8B) for more details on the model.

---
This repository contains the resources for our paper "DRT-o1: Optimized Deep Reasoning Translation via Long Chain-of-Thought"

Updates:
2024.12.31: We updated our paper with more detals and analyses. Check it out!
2024.12.31: We released the testing set of our work, please refer to data/test.jsonl
2024.12.30: We released a new model checkpoint using Llama-3.1-8B-Instruct as the backbone, i.e., 🤗 DRT-o1-8B
2024.12.24: We released our paper. Check it out!
2024.12.23: We released our model checkpoints. 🤗 DRT-o1-7B and 🤗 DRT-o1-14B.
If you find this work is useful, please consider cite our paper:

@article{wang2024drt,
  title={DRT-o1: Optimized Deep Reasoning Translation via Long Chain-of-Thought},
  author={Wang, Jiaan and Meng, Fandong and Liang, Yunlong and Zhou, Jie},
  journal={arXiv preprint arXiv:2412.17498},
  year={2024}
}

---
## 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 Triangle104/DRT-8B-Q4_K_S-GGUF --hf-file drt-8b-q4_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/DRT-8B-Q4_K_S-GGUF --hf-file drt-8b-q4_k_s.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 Triangle104/DRT-8B-Q4_K_S-GGUF --hf-file drt-8b-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/DRT-8B-Q4_K_S-GGUF --hf-file drt-8b-q4_k_s.gguf -c 2048
```