YugoGPT-Florida

• Developed by: datatab
• License: mit

🏆 Results

Results obtained through the Serbian LLM Evaluation Benchmark

<table> <tr> <th><strong>MODEL<strong></th> <th><strong>ARC-E<strong></th> <th><strong>ARC-C<strong></th> <th><strong>Hellaswag<strong></th> <th><strong>PiQA<strong></th> <th><strong>Winogrande<strong></th> <th><strong>BoolQ<strong></th> <th><strong>OpenbookQA<strong></th> <th><strong>OZ_EVAL<strong></th> <th>SCORE</th> </tr> <tr> <td><a href="https://huggingface.co/datatab/YugoGPT-Florida/">YugoGPT-Florida</a></td> <td><strong>0.6918<strong></td> <td><strong>0.5766<strong></td> <td><strong>0.4037<strong></td> <td><strong>0.7374<strong></td> <td><strong>0.5782<strong></td> <td><strong>0.8685<strong></td> <td><strong>0.5918<strong></td> <td><strong>0.7407<strong></td> <td><strong>64,85875<strong></td> </tr> <tr> <td><a href="https://huggingface.co/datatab/Yugo55A-GPT/">Yugo55A-GPT</a></td> <td>0.5846</td> <td>0.5185</td> <td>0.3686</td> <td>0.7076</td> <td>0.5277</td> <td>0.8584</td> <td>0.5485</td> <td>0.6883</td> <td>60,0275</td> </tr> <tr> <td><a href="https://huggingface.co/datatab/Yugo60-GPT">Yugo60-GPT</a></td> <td>0.4948</td> <td>0.4542</td> <td>0.3342</td> <td>0.6897</td> <td>0.5138</td> <td>0.8212</td> <td>0.5155</td> <td>0.6379</td> <td>55,76625</td> </tr> <tr> <td><a href="https://huggingface.co/datatab/Yugo45-GPT">Yugo45-GPT</a></td> <td>0.4049</td> <td>0.3900</td> <td>0.2812</td> <td>0.6055</td> <td>0.4992</td> <td>0.5793</td> <td>0.4433</td> <td>0.6111</td> <td>47,68125</td> </tr> </table>

🏋️ Training Stats

💻 Usage

!pip -q install git+https://github.com/huggingface/transformers

from IPython.display import HTML, display

def set_css():
  display(HTML('''
  <style>
    pre {
        white-space: pre-wrap;
    }
  </style>
  '''))
get_ipython().events.register('pre_run_cell', set_css)

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")

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)

generate("Nabroj mi sve planete suncevog sistemai reci mi koja je najveca planeta?")

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:

@article{YugoGPT-Florida},
  title={YugoGPT-Florida},
  author={datatab},
  year={2024},
  url={https://huggingface.co/datatab/YugoGPT-Florida}
}

<div id="zastava"> <div class="grb"> <img src="https://www.ai.gov.rs/img/logo_60x120-2.png" style="position:relative; left:30px; z-index:10; height:85px"> </div> <table width=100% style="border:0px"> <<tr style="background-color:#C6363C;width:100%;border:0px;height:30px"><td style="width:100vw"></td></tr> <tr style="background-color:#0C4076;width:100%;border:0px;height:30px"><td></td></tr> <tr style="background-color:#ffffff;width:100%;border:0px;height:30px"><td></td></tr> </table> </div> <style> .ffeat: { color:red } .cover { width: 100%; margin-bottom: 5pt } .highlight-container, .highlight { position: relative; text-decoration:none } .highlight-container { display: inline-block; } .highlight{ color:white; text-transform:uppercase; font-size: 16pt; } .highlight-container{ padding:5px 10px } .highlight-container:before { content: " "; display: block; height: 100%; width: 100%; margin-left: 0px; margin-right: 0px; position: absolute; background: #e80909; transform: rotate(2deg); top: -1px; left: -1px; border-radius: 20% 25% 20% 24%; padding: 10px 18px 18px 10px; } div.grb, #zastava>table { position:absolute; top:0px; left: 0px; margin:0px } div.grb>img, #zastava>table{ margin:0px } #zastava { position: relative; margin-bottom:120px } p { font-size:14pt } </style>