Cosmos LLaMa
This model is a fully fine-tuned version of the LLaMA-3 8B model with a 30GB Turkish dataset.
The Cosmos LLaMa is designed for text generation tasks, providing the ability to continue a given text snippet in a coherent and contextually relevant manner. Due to the diverse nature of the training data, which includes websites, books, and other text sources, this model can exhibit biases. Users should be aware of these biases and use the model responsibly.
Example Usage
Here is an example of how to use the model in colab:
!pip install -U accelerate bitsandbytes
import torch
from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
from transformers import BitsAndBytesConfig
import time
model_name = "ytu-ce-cosmos/Turkish-Llama-8b-v0.1"
bnb_config = BitsAndBytesConfig(
load_in_8bit=True,
bnb_8bit_compute_dtype=torch.bfloat16,
load_in_8bit_fp32_cpu_offload=True,
device_map = 'auto'
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto",
torch_dtype=torch.bfloat16,
quantization_config=bnb_config,
)
text_generator = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
device_map="auto",
temperature=0.3,
repetition_penalty=1.1,
top_p=0.9,
max_length=610,
do_sample=True,
return_full_text=False,
min_new_tokens=32
)
text = """Yapay zeka hakkında 3 tespit yaz.\n"""
r = text_generator(text)
print(r[0]['generated_text'])
"""
1. Yapay Zeka (AI), makinelerin insan benzeri bilişsel işlevleri gerçekleştirmesini sağlayan bir teknoloji alanıdır.
2. Yapay zekanın geliştirilmesi ve uygulanması, sağlık hizmetlerinden eğlenceye kadar çeşitli sektörlerde çok sayıda fırsat sunmaktadır.
3. Yapay zeka teknolojisinin potansiyel faydaları önemli olsa da mahremiyet, işten çıkarma ve etik hususlar gibi konularla ilgili endişeler de var.
"""
Acknowledgments
- Thanks to the generous support from the Hugging Face team, it is possible to download models from their S3 storage 🤗
- Computing resources used in this work were provided by the National Center for High Performance Computing of Turkey (UHeM) under grant numbers 1016912023 and 1018512024
- Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC)
Contact
COSMOS AI Research Group, Yildiz Technical University Computer Engineering Department https://cosmos.yildiz.edu.tr/ cosmos@yildiz.edu.tr
Citation
@inproceedings{kesgin2024optimizing,
title={Optimizing Large Language Models for Turkish: New Methodologies in Corpus Selection and Training},
author={Kesgin, H Toprak and Yuce, M Kaan and Dogan, Eren and Uzun, M Egemen and Uz, Atahan and {\.I}nce, Elif and Erdem, Yusuf and Shbib, Osama and Zeer, Ahmed and Amasyali, M Fatih},
booktitle={2024 Innovations in Intelligent Systems and Applications Conference (ASYU)},
pages={1--6},
year={2024},
organization={IEEE}
}