Transformers
PyTorch
Italian
xglm
Inference Endpoints
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  This model is a <b>conversational</b> language model for the <b>Italian</b> language, based on a GPT-like <b>[1]</b> architecture (more specifically, the model has been obtained by modifying Meta's XGLM architecture <b>[2]</b> and exploiting its 1.7B checkpoint).
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  The model has been trained on a corpus of \~50K Italian conversational exchanges for \~3 epochs (\~15K steps with a batch size of 10), using 3 different learning rates (1e-5, 2e-6, 1e-6) and exploiting FP16 quantization to manage the considerable size of the model.
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- The training corpus has been built by using Meta's Blenderbot <b>[3]</b> to generate 50K conversational exchanges in English, and then translating them to the Italian language using a machine traslation model.
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  The current release is designed for brief and informal conversations (small talk) covering light topics (mainly food, entertainment and holidays), but several generalizations and improvements will be introduced in future releases.
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  This model is a <b>conversational</b> language model for the <b>Italian</b> language, based on a GPT-like <b>[1]</b> architecture (more specifically, the model has been obtained by modifying Meta's XGLM architecture <b>[2]</b> and exploiting its 1.7B checkpoint).
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  The model has been trained on a corpus of \~50K Italian conversational exchanges for \~3 epochs (\~15K steps with a batch size of 10), using 3 different learning rates (1e-5, 2e-6, 1e-6) and exploiting FP16 quantization to manage the considerable size of the model.
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+ The training corpus has been built by using Meta's Blenderbot <b>[3]</b> to generate 50K conversational exchanges in English, and then translating them to the Italian language using a machine translation model.
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  The current release is designed for brief and informal conversations (small talk) covering light topics (mainly food, entertainment and holidays), but several generalizations and improvements will be introduced in future releases.
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