transformers gguf pytorch instruct finetune translation llama-cpp gguf-my-repo text-generation ko base_model:lemon-mint/Llama-3-Translation-8B-v0.180 base_model:quantized:lemon-mint/Llama-3-Translation-8B-v0.180 license:llama3 endpoints_compatible region:us conversational
---
base_model: lemon-mint/Llama-3-Translation-8B-v0.180
language:
- ko
library_name: transformers
license: llama3
pipeline_tag: text-generation
tags:
- pytorch
- instruct
- finetune
- translation
- llama-cpp
- gguf-my-repo
widget:
- messages:
  - role: user
    content: Translate into Korean:Hamsters don't eat cats.
---

# DarkClaw42/Llama-3-Translation-8B-v0.180-Q5_K_M-GGUF
This model was converted to GGUF format from [`lemon-mint/Llama-3-Translation-8B-v0.180`](https://huggingface.co/lemon-mint/Llama-3-Translation-8B-v0.180) 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/lemon-mint/Llama-3-Translation-8B-v0.180) for more details on the model.

Llama 3 Translation 8B v0.180
Eval Loss: 0.69922
Train Loss: 0.65752
lr: 8e-05
optimizer: adamw
lr_scheduler_type: cosine

#Prompt Template
<|begin_of_text|><|im_start|>user
Translate into Korean:Hamsters don't eat cats.<|im_end|>
<|im_start|>assistant
햄스터는 고양이를 먹지 않습니다.<|im_end|><|end_of_text|>

<|begin_of_text|><|im_start|>user
Translate into English:햄스터는 고양이를 먹지 않습니다.<|im_end|>
<|im_start|>assistant
Hamsters do not eat cats.<|im_end|><|end_of_text|>

## 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 DarkClaw42/Llama-3-Translation-8B-v0.180-Q5_K_M-GGUF --hf-file llama-3-translation-8b-v0.180-q5_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo DarkClaw42/Llama-3-Translation-8B-v0.180-Q5_K_M-GGUF --hf-file llama-3-translation-8b-v0.180-q5_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 DarkClaw42/Llama-3-Translation-8B-v0.180-Q5_K_M-GGUF --hf-file llama-3-translation-8b-v0.180-q5_k_m.gguf -p "<|begin_of_text|><|im_start|>user
Translate into Korean:Hamsters don't eat cats.<|im_end|>"
```
or 
```
./llama-server --hf-repo DarkClaw42/Llama-3-Translation-8B-v0.180-Q5_K_M-GGUF --hf-file llama-3-translation-8b-v0.180-q5_k_m.gguf -c 2048
```
