Tensor-2-40m-base

Tensor-2-40m-base is a Russian-language language model from the Tensor series, developed as part of the GribAI project. This is a base (pretrain) model without instruction tuning.

Description

Compared to previous models in the series, Tensor-2-40m-base shows noticeably better text continuation and stronger understanding of the Russian language — both grammatically and in terms of semantic coherence between sentences.

Training

The model was trained on 70 MB of Russian-language text data.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "VGribAI/Tensor-2-40m-base"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "Привет, как дела"
inputs = tokenizer(prompt, return_tensors="pt")
output = model.generate(**inputs, max_new_tokens=100)

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

Limitations

This is a base (pretrain) model with no dialogue alignment — it's meant for text continuation, not for answering questions or following instructions. GribAI project (VGribAI).

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Model size
40.4M params
Tensor type
F32
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