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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Train Loss: 2.4800
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- Validation Loss: 2.7320
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- Epoch: 4
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## Model description
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More information needed
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## Intended uses & limitations
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## Training procedure
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results: []
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# ChatGPT Prompt Generator v12
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This model is a fine-tuned version of [BART-large](https://huggingface.co/facebook/bart-large) on a ChatGPT prompts dataset.
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It achieves the following results on the evaluation set:
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It achieves the following results on the evaluation set:
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- Train Loss: 2.4800
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- Validation Loss: 2.7320
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- Epoch: 4
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## Intended uses & limitations
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You can use this to generate ChatGPT personas. Simply input a persona like below:
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```
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from transformers import BartForConditionalGeneration, BartTokenizer
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example_english_phrase = "photographer"
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batch = tokenizer(example_english_phrase, return_tensors="pt")
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generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
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output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
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```
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## Training procedure
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