chatgpt-prompt-generator-v12

Maintained By
merve

ChatGPT Prompt Generator v12

PropertyValue
Base ModelBART-large
LicenseApache 2.0
FrameworkTensorFlow 2.11.0
Training Datasetfka/awesome-chatgpt-prompts

What is chatgpt-prompt-generator-v12?

The chatgpt-prompt-generator-v12 is a specialized language model built on the BART-large architecture, specifically designed to generate ChatGPT personas and prompts. This model represents a fine-tuned version that has been trained on a curated dataset of ChatGPT prompts, achieving impressive training metrics with a final training loss of 2.48 and validation loss of 2.73.

Implementation Details

The model utilizes the BART architecture with AdamWeightDecay optimizer, implementing a learning rate of 2e-05 and weight decay rate of 0.01. Training was conducted over 5 epochs using float32 precision, showing consistent improvement in loss metrics throughout the training process.

  • Optimized with AdamWeightDecay (β1=0.9, β2=0.999)
  • Trained using Transformers 4.26.1 and TensorFlow 2.11.0
  • Supports conditional text generation with customizable output length

Core Capabilities

  • Generates contextually relevant ChatGPT personas
  • Supports batch processing for efficient prompt generation
  • Configurable maximum token generation (max_new_tokens parameter)
  • Easy integration with Transformers pipeline

Frequently Asked Questions

Q: What makes this model unique?

This model specializes in generating ChatGPT personas and prompts, trained specifically on a curated dataset of prompts. Its progressive training results demonstrate consistent improvement in generation quality, making it particularly effective for creating contextually appropriate ChatGPT interactions.

Q: What are the recommended use cases?

The model is ideal for generating creative ChatGPT personas, creating diverse prompt templates, and automating the process of crafting engaging conversational scenarios. It's particularly useful for developers and content creators who need to generate various ChatGPT interaction scenarios.

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