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---
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] -->
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- **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) |
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## Citation
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