ChatGPT Prompt Generator
This model is a fine-tuned version of BART-large on a ChatGPT prompts dataset. It achieves the following results on the evaluation set:

Train Loss: 2.8329
Validation Loss: 2.5015
Epoch: 4
Intended uses & limitations
You can use this to generate ChatGPT personas. Simply input a persona like below:

from transformers import BartForConditionalGeneration, BartTokenizer

example_english_phrase = "photographer"
batch = tokenizer(example_english_phrase, return_tensors="pt")
generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)

Training procedure
Training hyperparameters
The following hyperparameters were used during training:

optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32
https://huggingface.co/merve/chatgpt-prompts-bart-long

huggingface.co

merve/chatgpt-prompts-bart-long · Hugging Face

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