---
license: cc-by-nc-4.0
language:
- ro
base_model:
- google/gemma-7b
---

# Model Card for Model ID

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

RoGemma 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] -->
<!-- - **Shared by [optional]:** [More Information Needed] -->
<!-- - **Model type:** [More Information Needed] -->
- **Language(s):** Romanian
- **License:** cc-by-nc-4.0
- **Finetuned from model:** [gemma-7b](https://huggingface.co/google/gemma-7b)


### 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

RoGemma 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/RoGemma-7b-Instruct")
model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoGemma-7b-Instruct")

instruction = "Ce jocuri de societate pot juca cu prietenii mei?"
chat = [
        {"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|
|--------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
| google/gemma-1.1-7b-it| 41.39    | 40.05    | 47.12    | 54.62    | 47.10    | 9.73    | 49.75    |  
| *RoGemma-7b-Instruct*  | ***53.65***    | ***52.77***    | ***54.69***    | ***69.10***    | ***61.97***    | ***31.97***     | ***51.43***   |  


## MT-Bench

| Model              | Average  | 1st turn      | 2nd turn     | Answers in Ro |
|--------------------|:--------:|:--------:|:--------:|:--------:|
| google/gemma-1.1-7b-it    | 4.63    | 5.18    | 4.08    | **160 / 160**|
| *RoGemma-7b-Instruct*| ***4.83***|***5.56***| ***4.10*** |**160 / 160**|

## RoCulturaBench

| Model              | Score  | Answers in Ro|
|--------------------|:--------:|:--------:|
| google/gemma-1.1-7b-it   | **3.22**    | **100 / 100**  |
| *RoGemma-7b-Instruct*| *3.47*| ***100 / 100*** |



## RoGemma Model Family

| Model              | Link  |
|--------------------|:--------:|
|*RoGemma-7b-Instruct*| [link](https://huggingface.co/OpenLLM-Ro/RoGemma-7b-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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