18-Death/sq-rot13-bijection-ecqa
The 18-Death/sq-rot13-bijection-ecqa is a 3.1 billion parameter language model fine-tuned using the TRL framework. This model is designed for text generation tasks, offering a substantial 32,768 token context window. It was trained with Supervised Fine-Tuning (SFT) and is suitable for applications requiring extended conversational memory or processing of longer input sequences.
Loading preview...
Model Overview
The 18-Death/sq-rot13-bijection-ecqa is a 3.1 billion parameter language model, fine-tuned using the TRL framework. It features a significant context length of 32,768 tokens, making it suitable for tasks requiring extensive memory or processing of long documents.
Key Capabilities
- Text Generation: The model is primarily designed for generating text based on given prompts, as demonstrated by its quick start example for answering open-ended questions.
- Extended Context: With a 32,768 token context window, it can handle longer inputs and maintain coherence over extended conversations or documents.
- SFT Training: Trained with Supervised Fine-Tuning (SFT), indicating its optimization for specific instruction-following or response generation patterns.
Training Details
The model was trained using SFT, leveraging the TRL library. The development environment included TRL 1.3.0, Transformers 5.6.2, Pytorch 2.10.0, Datasets 4.8.4, and Tokenizers 0.22.2.
Good For
- Applications requiring text generation with a focus on maintaining context over long inputs.
- Developers looking for a fine-tuned model with a large context window for conversational AI or document summarization tasks.