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

# Model Card for Model ID

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

RoMistral 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:** [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)

<!-- - **Finetuned from model [optional]:** [More Information Needed] -->

### Model Sources

<!-- Provide the basic links for the model. -->

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

## Intended Use

### Intended Use Cases

RoMistral 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/RoMistral-7b-Instruct")
model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoMistral-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|
|--------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
| Mistral-7B-Instruct-v0.2| 45.63    | 43.09    | 44.87    | 59.26    | 54.12    | 10.86     | **61.56**    |  
| *RoMistral-7b-Instruct*  | ***52.49***    | ***50.39***    | ***51.64***    | ***66.69***    | ***60.24***    | ***33.71***     | 52.59    |  


## MT-Bench

| Model              | Average  | 1st turn      | 2nd turn     |
|--------------------|:--------:|:--------:|:--------:|
| Mistral-7B-Instruct-v0.2    | 5.84    | 6.06    | **5.63**    |
| *RoMistral-7b-Instruct*| ***5.92***|***6.53***| *5.415* |




## RoMistral Model Family

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


<!--
## Citation 

 If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section.

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]  -->