---
library_name: transformers
license: mit
datasets:
- MattCoddity/dockerNLcommands
language:
- en
old_version: Bruce1489/Llama3.2-docker-command-v2
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->

<h3>Improved accuracy over V2.</h3>
<h3>Fine-tuned the "meta-llama/Llama-3.2-1B-Instruct" model using the QLoRA technique. </h3>
<h3>The resulting model can generate Docker commands based on given statements.</h3>

- **Developed by:** Bruce1489(정성훈, Bruce Jung)
- **License:** mit
- **Finetuned from model [optional]:** meta-llama/Llama-3.2-1B-Instruct

### Direct Use
```python
import torch
from transformers import pipeline

pipe = pipeline(
    "text-generation",
    model="Bruce1489/Llama3.2-docker-command-v3",
    torch_dtype=torch.bfloat16,
    device_map="auto"
)
messages = [
    {"role": "system", "content": "translate this sentence in docker command"},
    {"role": "user", "content": "Please show me the Docker containers that have exited and are related to the mongo image."},
]

outputs = pipe(
    messages,
    max_new_tokens=256,
    temperature = 0.5,
    top_p  = 0.9,
    top_k = 10,
    do_sample = True,
    repetition_penalty = 1.2
)
print(outputs[0]["generated_text"][-1]['content'])

```