Bu model GPU NVIDIA V100 32GB va 0.53 GB malumotlarni kun.uz dan foydalanilgan holda Transfer Learning va Fine-tuning texnikasi asosida 1 kundan ziyod vaqt davomida o'qitilgan.

Qanday foydaniladi

python

  
from transformers import AutoTokenizer, AutoModelWithLMHead
import torch

tokenizer = AutoTokenizer.from_pretrained("rifkat/GPTuz")
model = AutoModelWithLMHead.from_pretrained("rifkat/GPTuz")

tokenizer.model_max_length=1024 

Bitta so'z yaratish

python

[object Object]
[object Object]
[object Object]

Bitta to'liq ketma-ketlikni yarating

python

text = "Covid-19 га қарши эмлаш бошланди, "
inputs = tokenizer(text, return_tensors="pt")


sample_outputs = model.generate(inputs.input_ids,
                                pad_token_id=50256,
                                do_sample=True, 
                                max_length=50, # kerakli token raqamini qo'ying
                                top_k=40,
                                num_return_sequences=1)


for i, sample_output in enumerate(sample_outputs):
    print(">> Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist())))

python

@misc {rifkat_davronov_2022,
	authors       = { {Adilova Fatima,Rifkat Davronov, Samariddin Kushmuratov, Ruzmat Safarov} },
	title        = { GPTuz (Revision 2a7e6c0) },
	year         = 2022,
	url          = { https://huggingface.co/rifkat/GPTuz },
	doi          = { 10.57967/hf/0143 },
	publisher    = { Hugging Face }
}