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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. -->
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. -->
RoLlama2 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 [optional]:** [More Information Needed] -->
### Model Sources
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/OpenLLM-Ro/llama-recipes
- **Paper:** [More Information Needed]
## 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 = "Write me a poem about Machine Learning."
input_ids = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**input_ids)
print(tokenizer.decode(outputs[0]))
```
## Benchmarks
| Model | Average | ARC | MMLU |Winogrande|HellaSwag | GSM8k |TruthfulQA|
|--------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
| Llama-2-7b | 35.65 | 33.85 | 30.93 | 56.43 | 46.98 | 1.37 | 44.36 |
| *RoLlama2-7b-Base* | *38.32* | *35.83* | *30.47* | *60.16* | *55.52* | *2.17* | *45.78* |
| Llama-2-7b-chat | 35.58 | 34.92 | 32.37 | 54.26 | 44.52 | 2.05 | 45.38 |
|RoLlama2-7b-Instruct| **44.42**|**40.36** |**37.41** |**69.58** | 55.64 | **17.59**| 45.96 |
|RoLlama2-7b-Chat | 42.65 | 38.29 | 35.27 | 65.25 | **56.45**| 12.84 | **47.79**|
## MT-Bench
| Model | Average | 1st turn | 2nd turn |
|--------------------|:--------:|:--------:|:--------:|
| Llama-2-7b-chat | 1.70 | 2.00 | 1.41 |
|RoLlama2-7b-Instruct| **4.31**|**5.66** | 2.95 |
|RoLlama2-7b-Chat | 3.91 | 4.25 | **3.57** |
## 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
<!-- 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]
|