A state-of-the-art language model for Russian language processing. This checkpoint contains a preliminary version of the model with 4 billion parameters.
1from transformers import AutoTokenizer, AutoModelForCausalLM
2import torch
3
4tokenizer = AutoTokenizer.from_pretrained("aeonium/Aeonium-v1.1-Base-4B")
5model = AutoModelForCausalLM.from_pretrained("aeonium/Aeonium-v1.1-Base-4B").cuda()
6
7input_ids = tokenizer("Искусственный интеллект - это", return_tensors='pt').to(model.device)["input_ids"]
8output = model.generate(input_ids, max_new_tokens=48, do_sample=True, temperature=0.7)
9print(tokenizer.decode(output[0]))
The dataset for pre-training is collected from public data, most of which are web pages in Russian.
The training is performed thanks to a grant from
TPU Research Cloud on a TPU v4-256 node.
Aeonium v1.1 is a large language model trained on a broad dataset from the internet. As such, it may generate text that contains biases, offensive language, or other disapproving content. The model outputs should not be considered factual or representative of any individual's beliefs or identity. Users should exercise caution and apply careful filtering when using Aeonium's generated text, especially for sensitive or high-stakes applications. The developers do not condone generating harmful, biased, or unethical content.
The model is released under the Apache 2.0 license.
