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aeonium/Aeonium-v1-Base-1.6B-checkpoint-20B
Aeonium-v1-Base-1.6B-checkpoint-20B is a text generation model from aeonium. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
A state-of-the-art language model for Russian language processing. This checkpoint contains a preliminary version of the model with 1.6 billion parameters. Trained only on web pages.
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.safetensors6.5 GB · 100%
From the Hugging Face model README
A state-of-the-art language model for Russian language processing. This checkpoint contains a preliminary version of the model with 1.6 billion parameters. Trained only on web pages.
| Name | N of parameters | N of dataset tokens | Context window |
|---|---|---|---|
| Aeonium-v1-BaseWeb-1B | 1.6B | 32B | 4K |
| Aeonium-v1-Base-1B | 1.6B | In training | 4K |
| Aeonium-v1-Chat-1B | 1.6B | In training | 4K |
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("aeonium/Aeonium-v1-Base-1.6B-checkpoint-20B")
model = AutoModelForCausalLM.from_pretrained("aeonium/Aeonium-v1-Base-1.6B-checkpoint-20B").cuda()
input_ids = tokenizer("Искусственный интеллект - это", return_tensors='pt').to(model.device)["input_ids"]
output = model.generate(input_ids, max_new_tokens=48, do_sample=True, temperature=0.7)
print(tokenizer.decode(output[0]))
Output:
Искусственный интеллект - это основа современной науки и техники. Его потенциал позволяет решать задачи, которые выходят за пределы человеческих возможностей. В работе над ними участвуют все: от ученых до инженеров и даже военных. В своей книге "Искусственный интеллект" автор книги, профессор Л
The dataset for pre-training is collected from public data, most of which are web pages in Russian. The total size of the data is 20B tokens.
The training is performed thanks to a grant from TPU Research Cloud on a TPU v4-32 node.
The model is released under the Apache 2.0 license.