readme: ---
  language:
  - ru
  tags:
  - causal-lm
  - text-generation
  license:
  - apache-2.0
  inference: false
  widget:
  - text: "Как обрести просветление?<s>"
    example_title: "Википедия"
  ---
  # RuGPT3Medium-tathagata
  ## Model description
  This is the model for text generation for Russian based on [rugpt3medium_based_on_gpt2](https://huggingface.co/sberbank-ai/rugpt3medium_based_on_gpt2).
  ## Intended uses & limitations
  Тhis model was trained and run to generate text on RTX 3080
  #### How to use
  ```python
  from transformers import GPT2LMHeadModel, GPT2Tokenizer
  import torch
  DEVICE = torch.device("cuda:0")
  
  model_name_or_path = "radm/rugpt3medium-tathagata"
  tokenizer = GPT2Tokenizer.from_pretrained("sberbank-ai/rugpt3medium_based_on_gpt2")
  model = GPT2LMHeadModel.from_pretrained(model_name_or_path).to(DEVICE)
  
  text = "В чем смысл жизни?\n"
  input_ids = tokenizer.encode(text, return_tensors="pt").to(DEVICE)
  model.eval()
  with torch.no_grad():
      out = model.generate(input_ids, 
                          do_sample=True,
                          num_beams=4,
                          temperature=1.1,
                          top_p=0.9,
                          top_k=50,
                          max_length=250,
                          min_length=50,
                          early_stopping=True,
                          no_repeat_ngram_size=2
                          )
  
  generated_text = list(map(tokenizer.decode, out))[0]
  print()
  print(generated_text)
  ```
  
  ## Dataset
  
  Dataset based on summaries of major Buddhist, Hindu and Advaita texts such as:
  
  - Diamond Sutra
  - Lankavatara Sutra
  - Sri Nisargadatta Maharaj quotes
  - Quotes from the Bhagavad Gita
  
  Dataset link: [tathagata](https://huggingface.co/datasets/radm/tathagata)
  