metadata

language:
  - sr
tags:
  - Srpski
  - Serbian
  - GPT2
  - generisanje
  - generation
name:
  - Serbian-GPT-2

GPT-2 Model Trained on Serbian Corpus

By sharing this model, we aim to foster further research and applications in Serbian language processing.

Introduction:

This GPT-2 model has been tuned on an extensive Serbian corpus, boasting a richness of 43 million tokens. It is designed to generate high-quality text in Serbian, capturing the nuances and intricacies of the language.

Dataset Details:

The dataset encompasses a diverse range of topics, representing various aspects of the Serbian language and culture. Size: 43 million tokens.

Model Usage:

This model can be utilized for various NLP tasks such as text generation, summarization, translation, and more. Due to its comprehensive training on a vast corpus, it promises accurate and contextually relevant outputs, especially for tasks related to the Serbian language.

Download and Decryption the Model:

import os
import requests
from transformers import GPT2LMHeadModel
from cryptography.fernet import Fernet

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'

print("\nDownload Serbian-GPT-2 model...")

# Download Serbian-GPT-2 model
model_name = 'edukom/Serbian-GPT-2'
base_url = f'https://huggingface.co/{model_name}/resolve/main/'
files_to_download = ['added_tokens.json', 'config.json', 'generation_config.json', 'merges.txt', 'pytorch_model.bin', 'special_tokens_map.json', 'tokenizer.json', 'tokenizer_config.json', 'vocab.json']

cache_dir = 'path/to/where/you/want/to/store/the/model'

for file in files_to_download:
    response = requests.get(base_url + file)
    with open(os.path.join(cache_dir, file), 'wb') as f:
        f.write(response.content)

# Decryption pytorch_model.bin
key = input("\nEnter the decryption key: ").encode()
cipher_suite = Fernet(key)

decryption_data = os.path.join(cache_dir, 'pytorch_model.bin')

try:
    with open(decryption_data, 'rb') as file:
        encrypted_data = file.read()

    decrypted_data = cipher_suite.decrypt(encrypted_data)

    with open(decryption_data, 'wb') as file:
        file.write(decrypted_data)

    # Loading Serbian-GPT-2 model
    model = GPT2LMHeadModel.from_pretrained(cache_dir)
    print("\nCongratulations, the Serbian-GPT-2 model is ready for use ヅ\n")

except Exception as e:
    print(f"\nError during decryption: {e}")
    print("\nYou can decrypt the model by contacting the author of this model who will add the key, email: info@edukom.rs")

# Now you can use the Serbian-GPT-2 model for further operations...

Licensing:

The author of this model is the company Edukom AI. The model is protected by encryption and its use requires a decryption key. Please check the licensing terms if you intend to use the model for commercial purposes. For any questions or if you need decryption keys, feel free to contact us at info@edukom.rs