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---
license: llama2
language:
- ro
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
RoLlama2 is a family of pretrained and fine-tuned generative text models for Romanian. This is the repository for the **foundational 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 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] -->
<!-- - **Shared by [optional]:** [More Information Needed] -->
<!-- - **Model type:** [More Information Needed] -->
- **Language(s):** Romanian
- **License:** Llama2 Community License Agreement
- **Continual pretrained from model:** [Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b-hf)
### Model Sources
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/OpenLLM-Ro/llama-recipes
- **Paper:** https://arxiv.org/abs/2406.18266
## Intended Use
### Intended Use Cases
RoLlama2 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/RoLlama2-7b-Base")
model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoLlama2-7b-Base")
input_text = "Mihai Eminescu a fost "
input_ids = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**input_ids, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))
```
## Benchmarks
| Model | Average | ARC | MMLU |Winogrande|HellaSwag | GSM8k |TruthfulQA|
|--------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
| Llama-2-7b | 37.11 | 36.09 | **33.67** | 57.60 | 48.00 | **5.08** | 42.23 |
| *RoLlama2-7b-Base* | ***38.03*** | ***37.95*** | *27.22* | ***59.29*** | ***57.22*** | *2.53* | ***44.00*** |
## RoLlama2 Model Family
| Model | Link |
|--------------------|:--------:|
|*RoLlama2-7b-Base* | [link](https://huggingface.co/OpenLLM-Ro/RoLlama2-7b-Base) |
|RoLlama2-7b-Instruct| [link](https://huggingface.co/OpenLLM-Ro/RoLlama2-7b-Instruct) |
|RoLlama2-7b-Chat | [link](https://huggingface.co/OpenLLM-Ro/RoLlama2-7b-Chat) |
## 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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