---
license: cc-by-nc-4.0
language:
- ro
---

# Model Card for Model ID

*Built with Meta Llama 3*


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RoLlama3 is a family of pretrained and fine-tuned generative text models for Romanian. This is the repository for the **instruct 7B model**. Links to other models can be found at the bottom of this page.


## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->
OpenLLM-Ro represents the first open-source effort to build a LLM specialized for Romanian. OpenLLM-Ro developed and publicly releases a collection of Romanian LLMs, both in the form of foundational model and instruct and chat variants.


- **Developed by:** OpenLLM-Ro
<!-- - **Funded by [optional]:** [More Information Needed] -->
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<!-- - **Model type:** [More Information Needed] -->
- **Language(s):** Romanian
- **License:** cc-by-nc-4.0
- **Finetuned from model:** [Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)


### Model Sources

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- **Repository:** https://github.com/OpenLLM-Ro/llama-recipes
- **Paper:** https://arxiv.org/abs/2406.18266

## Intended Use

### Intended Use Cases

RoLlama3 is intented for research use in Romanian. Base models can be adapted for a variety of natural language tasks while instruction and chat tuned models are intended for assistant-like chat.

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->

Use in any manner that violates the license, any applicable laws or regluations, use in languages other than Romanian.



## How to Get Started with the Model

Use the code below to get started with the model.

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("OpenLLM-Ro/RoLlama3-8b-Instruct")
model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoLlama3-8b-Instruct")

instruction = "Ce jocuri de societate pot juca cu prietenii mei?"
chat = [
        {"role": "system", "content": "Ești un asistent folositor, respectuos și onest. Încearcă să ajuți cât mai mult prin informațiile oferite, excluzând răspunsuri toxice, rasiste, sexiste, periculoase și ilegale."},
        {"role": "user", "content": instruction},
        ]
prompt = tokenizer.apply_chat_template(chat, tokenize=False, system_message="")

inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
outputs = model.generate(input_ids=inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0]))
```

## Benchmarks

| Model              | Average  | ARC      | MMLU     |Winogrande|HellaSwag | GSM8k    |TruthfulQA|
|--------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
| Llama-3-8B-Instruct| 50.15     | 43.73     | 49.02    | 59.35    | 53.16    | **44.12**    | 51.52    |  
| *RoLlama3-8b-Instruct*  | ***50.61***    | ***44.66***    | ***52.19***    | ***67.58***    | ***57.65***    | *30.20*     | ***51.39***   |  

        


## MT-Bench

| Model              | Average  | 1st turn      | 2nd turn     |  Answers in Ro |
|--------------------|:--------:|:--------:|:--------:|:--------:|
| Llama-3-8B-Instruct    | **5.92**    | **6.36**    | **5.49**    | 158 / 160
| *RoLlama3-8b-Instruct*| *5.28* |*6.10*| *4.45* | ***160 / 160*** |



## RoCulturaBench

| Model              | Score  | Answers in Ro|
|--------------------|:--------:|:--------:|
| Llama-3-8B-Instruct   | **4.61**    | **100 / 100**  |
| *RoLlama3-8b-Instruct*| *3.83*| ***100 / 100*** |



## RoLlama3 Model Family

| Model              | Link  |
|--------------------|:--------:|
|*RoLlama3-8b-Instruct*| [link](https://huggingface.co/OpenLLM-Ro/RoLlama3-8b-Instruct) |


## Citation 

```
@misc{masala2024vorbecstiromanecsterecipetrain,
      title={"Vorbe\c{s}ti Rom\^ane\c{s}te?" A Recipe to Train Powerful Romanian LLMs with English Instructions}, 
      author={Mihai Masala and Denis C. Ilie-Ablachim and Alexandru Dima and Dragos Corlatescu and Miruna Zavelca and Ovio Olaru and Simina Terian-Dan and Andrei Terian-Dan and Marius Leordeanu and Horia Velicu and Marius Popescu and Mihai Dascalu and Traian Rebedea},
      year={2024},
      eprint={2406.18266},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2406.18266}, 
}
```
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