llama-600M-rus

Simple and customized amateur experimental model pretrained on approximately 60 Mb of text fiction books from the scratch.
It could generate amateur, but more or less adequate output as well (in respect of training tokens).
The work can be used as a checkpoint for the further training or for experiments.

Simple usage example:

from transformers import LlamaTokenizerFast, LlamaForCausalLM
model = LlamaForCausalLM.from_pretrained('demetera/llama-600M-rus')
tokenizer = LlamaTokenizerFast.from_pretrained('demetera/llama-600M-rus')

prompt = "Я вышел и улицу и"
inputs = tokenizer(prompt, return_tensors='pt')
outputs = model.generate(inputs.input_ids, attention_mask = inputs.attention_mask, max_new_tokens=250, do_sample=True, top_k=50, top_p=0.95)

print (tokenizer.decode(outputs[0], skip_special_tokens=True))