Tensor (1-2 sep. by parameters)
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outdated models • 7 items • Updated
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.
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.
The model was trained on 70 MB of Russian-language text data.
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))
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).