huggingtweets/____devii

The model is based on a pre-trained GPT-2 which is fine-tuned on @____devii's tweets . The data is tracked with W&B artifacts at every step of the pipeline . You can use this model directly with a pipeline for text generation: pipeline('text-generation') model='huggingtweets/_____devii') model('My dream is', num_return_sequences=5) model="HuggingTweets" model="My dream was", num_response_sequence=5" Model was trained on Twitter user @_devii and trained on data from the pre-training GPT2 . The model suffers,