introduction_en.ipynb

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    "## Overview\n",
    "\n",
    "This is an updated version of cointegrated/rubert-tiny: a small Russian BERT-based encoder with high-quality sentence embeddings. This [post in Russian](https://habr.com/ru/post/669674/) gives more details.\n"
   ]
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    "The differences from the previous version include:\n",
    "- a larger vocabulary: 83828 tokens instead of 29564;\n",
    "- larger supported sequences: 2048 instead of 512;\n",
    "- sentence embeddings approximate LaBSE closer than before;\n",
    "- meaningful segment embeddings (tuned on the NLI task)\n",
    "- the model is focused only on Russian.\n"
   ]
  },
  {
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    "The model should be used as is to produce sentence embeddings (e.g. for KNN classification of short texts) or fine-tuned for a downstream task.\n"
   ]
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    "Sentence embeddings can be produced as follows:\n"
   ]
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   "source": [
    "## how to use"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c98c0cce",
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   "source": [
    "!pip install --upgrade paddlenlp"
   ]
  },
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   "source": [
    "import paddle\n",
    "from paddlenlp.transformers import AutoModel\n",
    "\n",
    "model = AutoModel.from_pretrained(\"cointegrated/rubert-tiny2\")\n",
    "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
    "print(model(input_ids))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33dbe378",
   "metadata": {},
   "source": [
    "> The model introduction and model weights originate from [https://huggingface.co/cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) and were converted to PaddlePaddle format for ease of use in PaddleNLP.\n"
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