---
library_name: transformers
tags: []
---

# Model Card for Model ID

## Model Details

### Model Description

RoQLlama is a new lightweight Romanian language-adapted LLM with 7 billion parameters and quantized to 4 bits by employing the state-of-the-art quantized
LoRA (QLoRA) training technique.

- **Language:** Romanian
- **License:** Llama2 Community License Agreement
- **Finetuned from model:** Meta's Llama2 7B

### Model Sources
- **Paper:** https://arxiv.org/abs/2410.04269

## How to Get Started with the Model

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
MODEL_NAME = "andreidima/Llama-2-7b-Romanian-qlora"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, device_map="auto")
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map="auto")

input_text = """Eu răspund la întrebări pe baza contextului.
Context: În anul 1600, Mihai Viteazul a realizat prima unire a Țărilor Române: Țara Românească, Transilvania și Moldova. Această unire a fost un moment important în istoria României.
Întrebare: În ce an a realizat Mihai Viteazul prima unire a Țărilor Române?
Răspuns: """
input_ids = tokenizer(input_text, return_tensors="pt")

outputs = model.generate(
    **input_ids, 
    max_new_tokens=100, 
    eos_token_id=[13] # 13 is the token ID for a newline character at the end of a non-empty line
)
print(tokenizer.decode(outputs[0]))
```

Note: Adding a space at the end of the prompt has been observed to significantly improve the model's output quality.

## Training Details and Evaluation

Please refer to the paper for details on the model's training and evaluation.


## Citation

**BibTeX:**

```
@inproceedings{dima2024roqllama,
      title={RoQLlama: A Lightweight Romanian Adapted Language Model}, 
      author={George-Andrei Dima and Andrei-Marius Avram and Cristian-George Crăciun and Dumitru-Clementin Cercel},
      booktitle={Findings of the Association for Computational Linguistics: EMNLP 2024}
      year={2024},
      url={https://arxiv.org/abs/2410.04269}, 
}
```

**APA:**

Dima, G. A., Avram, A. M., Crăciun, C. G., & Cercel, D. C. (2024). RoQLlama: A lightweight Romanian adapted language model. In _Findings of the Association for Computational Linguistics: EMNLP 2024_.