README.md

---
license: cc-by-nc-4.0
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 **chat 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] -->
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- **Language(s):** Romanian
- **License:** cc-by-nc-4.0
- **Finetuned from model:** [RoLlama2-7b-Base](https://huggingface.co/OpenLLM-Ro/RoLlama2-7b-Base)

### Model Sources

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- **Repository:** https://github.com/OpenLLM-Ro/llama-recipes
- **Paper:** https://arxiv.org/abs/2405.07703

## 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-Chat")
model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoLlama2-7b-Chat")

instruction = "Care este cel mai înalt vârf muntos din România?"
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)

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-2-7b-chat    | 38.03    | 37.95    | 27.22    | 59.29    | 57.22    | 2.53     | 44.00    |  
|RoLlama2-7b-Instruct|**45.71**|**43.66**|**39.70**|**70.34** | 57.36  |**18.78**| 44.44    |  
|*RoLlama2-7b-Chat*    | *43.82*    | *41.92*    | *37.29*    | *66.68*    | ***57.91***| *13.47*    | ***45.65***|  



## MT-Bench

| Model              | Average  | 1st turn      | 2nd turn     | Answers in Ro |
|--------------------|:--------:|:--------:|:--------:|:--------:|
| Llama-2-7b-chat    | 1.21    | 1.68    | 0.74    | 44 / 160 |
|RoLlama2-7b-Instruct| **3.70**|**4.74**| **2.66** | **160 / 160** |
|*RoLlama2-7b-Chat*    | *TBC*    | *TBC*    | *TBC*    | *TBC* |

## RoCulturaBench

| Model              | Score  | Answers in Ro|
|--------------------|:--------:|:--------:|
| Llama-2-7b-chat    | 1.72    | 48 / 100   |
|RoLlama2-7b-Instruct| **3.43**| **160 / 160** |
|*RoLlama2-7b-Chat*    | *TBC*    | *TBC*    |




## 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{masala2024openllmrotechnicalreport,
      title={OpenLLM-Ro -- Technical Report on Open-source Romanian LLMs}, 
      author={Mihai Masala and Denis C. Ilie-Ablachim and Dragos Corlatescu and Miruna Zavelca and Marius Leordeanu and Horia Velicu and Marius Popescu and Mihai Dascalu and Traian Rebedea},
      year={2024},
      eprint={2405.07703},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2405.07703}, 
}
```
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