MU-NLPC
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CzeGPT-2_summarizer

Text Generation

text-generation-inference

Inference Endpoints

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hajekad commited on Apr 4, 2022

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 # CzeGPT-2_summarizer
-CzeGPT-2_summarizer is a Czech summarizer built upon the <a href="https://huggingface.co/MU-NLPC/CzeGPT-2">CzeGPT-2</a> model. The model has the same architectural dimensions as the GPT-2 small (12 layers, 12 heads, 1024 tokens on input/output, and embedding vectors with 768 dimensions) resulting in 124M trainable parameters. It was fine-tuned and evaluated on the <a href="https://aclanthology.org/L18-1551.pdf">SumeCzech</a> summarization dataset containing about 1M Czech news articles.
 The model is trained to generate the summary as long as you let it (or it runs out of sequence length). This leaves a space for developers to set their own constraints.
 ## Tokenizer

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 # CzeGPT-2_summarizer
+CzeGPT-2 summarizer is a Czech summarizer built upon the <a href="https://huggingface.co/MU-NLPC/CzeGPT-2">CzeGPT-2</a> model. The model has the same architectural dimensions as the GPT-2 small (12 layers, 12 heads, 1024 tokens on input/output, and embedding vectors with 768 dimensions) resulting in 124M trainable parameters. It was fine-tuned and evaluated on the <a href="https://aclanthology.org/L18-1551.pdf">SumeCzech</a> summarization dataset containing about 1M Czech news articles.
 The model is trained to generate the summary as long as you let it (or it runs out of sequence length). This leaves a space for developers to set their own constraints.
 ## Tokenizer