Distilgpt2

DistilGPT2 is a smaller and easier-to-run version of the GPT-2 model. It is trained using knowledge distillation and has similar functionality to GPT-2. It was trained on the OpenWebTextCorpus dataset and tokenized using a byte-level version of Byte Pair Encoding. DistilGPT2 performs slightly worse than GPT-2 on the WikiText-103 benchmark. The carbon emissions of training the model were estimated using a machine learning impact calculator.

Use cases

DistilGPT2 has a range of potential use cases for researchers and developers. Its smaller size and ease of use make it suitable for those looking to better understand and study large-scale generative language models. Additionally, DistilGPT2 can be utilized to build applications such as chatbots, virtual assistants, or content generators. Its ability to generate text makes it an invaluable tool for tasks such as language translation, summarization, and text completion. One practical use case for this model is the Write With Transformers web app, developed by the Hugging Face team, which allows users to interact with and generate text using DistilGPT2 directly from their browser. With further exploration and experimentation, this model has the potential to fuel the development of innovative and creative AI applications.