chatgpt-gpt4-prompts-bart-large-cnn-samsum
| Property | Value |
|---|---|
| License | MIT |
| Framework | TensorFlow 2.11.0 |
| Base Model | BART-large-CNN-samsum |
| Best Train Loss | 1.2214 |
What is chatgpt-gpt4-prompts-bart-large-cnn-samsum?
This is a specialized language model fine-tuned on the awesome-chatgpt-prompts dataset to generate high-quality prompts for ChatGPT, GPT-4, and other large language models. Built upon the BART-large-CNN architecture, it has been optimized through 5 epochs of training to achieve optimal prompt generation capabilities.
Implementation Details
The model utilizes the AdamWeightDecay optimizer with a learning rate of 2e-05 and implements float32 precision training. It achieved significant improvement in training loss from 3.1982 to 1.2214 over 5 epochs, demonstrating effective learning of prompt generation patterns.
- Built on BART-large-CNN architecture
- Incorporates TensorFlow 2.11.0 and Transformers 4.27.3
- Includes Streamlit Web UI support
- Optimized with AdamWeightDecay optimizer
Core Capabilities
- Generation of contextually relevant prompts for AI models
- Optimization for ChatGPT and GPT-4 interactions
- Web-based interface through Hugging Face Spaces
- Efficient prompt synthesis with controlled parameters
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in generating AI prompts by combining BART's summarization capabilities with specific fine-tuning on ChatGPT prompts, achieving a remarkable final training loss of 1.2214.
Q: What are the recommended use cases?
The model is ideal for developers and users who need to generate effective prompts for ChatGPT, GPT-4, or similar language models, particularly through its user-friendly Streamlit interface.
