
Base model: [gpt2-large](https://huggingface.co/gpt2-large)

Fine-tuned to generate responses on a dataset of [Vaccine public health tweets](https://github.com/TheRensselaerIDEA/generative-response-modeling). For more information about the dataset, task and training, see [our paper](https://arxiv.org/abs/2204.04353). This checkpoint corresponds to the lowest validation perplexity (2.82 at 2 epochs) seen during training. See Training metrics for Tensorboard logs.

For input format and usage examples, see our [COVID-19 public health tweet response model](https://huggingface.co/TheRensselaerIDEA/gpt2-large-covid-tweet-response).


{"license": "mit"}
transformers pytorch tensorboard gpt2 text-generation arxiv:2204.04353 license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #arxiv-2204.04353 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


Base model: gpt2-large

Fine-tuned to generate responses on a dataset of Vaccine public health tweets. For more information about the dataset, task and training, see our paper. This checkpoint corresponds to the lowest validation perplexity (2.82 at 2 epochs) seen during training. See Training metrics for Tensorboard logs.

For input format and usage examples, see our COVID-19 public health tweet response model.


TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #arxiv-2204.04353 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

passage: TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #arxiv-2204.04353 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
