---
license: mit
datasets:
- datatab/SrpWikiDataset
- datatab/open-orca-slim-serbian
language:
- sr
base_model:
- datatab/Yugo55A-GPT
---
- **Developed by:** datatab
- **License:** mit
## 🏆 Results
> Results obtained through the [**Serbian LLM Evaluation Benchmark**](https://huggingface.co/datasets/datatab/serbian-llm-benchmark)
| MODEL |
ARC-E |
ARC-C |
Hellaswag |
PiQA |
Winogrande |
BoolQ |
OpenbookQA |
OZ_EVAL |
SCORE |
| YugoGPT-Florida |
0.6918 |
0.5766 |
0.4037 |
0.7374 |
0.5782 |
0.8685 |
0.5918 |
0.7407 |
64,85875 |
| Yugo55A-GPT |
0.5846 |
0.5185 |
0.3686 |
0.7076 |
0.5277 |
0.8584 |
0.5485 |
0.6883 |
60,0275 |
| Yugo60-GPT |
0.4948 |
0.4542 |
0.3342 |
0.6897 |
0.5138 |
0.8212 |
0.5155 |
0.6379 |
55,76625 |
| Yugo45-GPT |
0.4049 |
0.3900 |
0.2812 |
0.6055 |
0.4992 |
0.5793 |
0.4433 |
0.6111 |
47,68125 |
# 🏋️ Training Stats
## 💻 Usage
```terminal
!pip -q install git+https://github.com/huggingface/transformers
```
```python
from IPython.display import HTML, display
def set_css():
display(HTML('''
'''))
get_ipython().events.register('pre_run_cell', set_css)
```
```python
import torch
import transformers
from transformers import AutoTokenizer, MistralForCausalLM
device = "cuda" if torch.cuda.is_available() else "cpu"
model = MistralForCausalLM.from_pretrained(
"datatab/YugoGPT-Florida",
torch_dtype="auto"
).to(device)
tokenizer = AutoTokenizer.from_pretrained("datatab/YugoGPT-Florida")
```
```python
from typing import Optional
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
def generate(
user_content: str, system_content: Optional[str] = ""
) -> str:
system_content = """Ispod se nalazi uputstvo koje definiše zadatak, zajedno sa unosom koji pruža dodatni kontekst.
Na osnovu ovih informacija, napišite odgovor koji precizno i tačno ispunjava zahtev.
"""
messages = [
{
"role": "system",
"content": system_content,
},
{"role": "user", "content": user_content},
]
tokenized_chat = tokenizer.apply_chat_template(
messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
).to("cuda")
text_streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
output = model.generate(
tokenized_chat,
streamer=text_streamer,
max_new_tokens=2048,
temperature=0.1,
repetition_penalty=1.11,
top_p=0.92,
top_k=1000,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id,
do_sample=True,
)
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
```
```python
generate("Nabroj mi sve planete suncevog sistemai reci mi koja je najveca planeta?")
```
```terminal
Sunčev sistem sadrži osam planeta: Merkur, Venera, Zemlja, Mars, Jupiter, Saturn, Uran i Neptun. Najveća planeta u Sunčevom sistemu je Jupiter.
```
## 💡 Contributions Welcome!
Have ideas, bug fixes, or want to add a custom model? We'd love for you to be part of the journey! Contributions help grow and enhance the capabilities of the **YugoGPT-Florida**.
## 📜 Citation
Thanks for using **YugoGPT-Florida** — where language learning models meet Serbian precision and creativity! Let's build smarter models together. 🚀�
If you find this model useful in your research, please cite it as follows:
```bibtex
@article{YugoGPT-Florida},
title={YugoGPT-Florida},
author={datatab},
year={2024},
url={https://huggingface.co/datatab/YugoGPT-Florida}
}
```
