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---
language:
- ru
license: apache-2.0
pipeline_tag: text-generation
tags:
- aeonium
inference:
parameters:
temperature: 0.8
---
# Aeoinum v1 BaseWeb 1B
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.
## Models
| 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 |
## Usage
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("aeonium/Aeonium-v1-BaseWeb-1B")
model = AutoModelForCausalLM.from_pretrained("aeonium/Aeonium-v1-BaseWeb-1B").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 не только про компьютеры и смартфоны. Его возможности безграничны, а с развитием интернета и интернета вещей он становится еще и самым настоящим оружием в борьбе с преступностью.
Мы поговорили с юристом о самых интересных и опасных способах использования ИИ.
```
## Dataset Detail
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 32B tokens.
## Training Detail
The training is performed thanks to a grant from [TPU Research Cloud](https://sites.research.google/trc/about/) on a TPU v4-128 node.
Loss: 2.68; Accuracy: 0.48; Batch Size: 1024
## Copyright
The model is released under the Apache 2.0 license. |