YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

license: mit datasets: - datatab/SrpWikiDataset - datatab/open-orca-slim-serbian language: - sr base_model: - datatab/Yugo55A-GPT

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  • Developed by: datatab
  • License: mit

πŸ† Results

Results obtained through the Serbian LLM Evaluation 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

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πŸ‹οΈ Training Stats

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πŸ’» Usage

*** Released with permission by datatab *** - GGUF quantized by @MarkoRadojcic

πŸ’‘ 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.

πŸ“œ Citation

Thanks for using YugoGPT-Florida β€” where language learning models meet Serbian precision and creativity! Let's build smarter models together. πŸš€οΏ½

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}
}
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