18-Death/sq-walnut53-rot13-gsm8k
The 18-Death/sq-walnut53-rot13-gsm8k is a 3.1 billion parameter causal language model fine-tuned by 18-Death using the TRL framework. This model is designed for text generation tasks, particularly conversational responses, and has a context length of 32768 tokens. It was trained using Supervised Fine-Tuning (SFT) to enhance its ability to generate coherent and relevant text based on prompts.
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Overview
The 18-Death/sq-walnut53-rot13-gsm8k is a 3.1 billion parameter language model developed by 18-Death. It is a fine-tuned variant, specifically trained using the Supervised Fine-Tuning (SFT) method within the TRL (Transformers Reinforcement Learning) framework. This model is equipped with a substantial context length of 32768 tokens, allowing it to process and generate longer sequences of text while maintaining coherence.
Key Capabilities
- Text Generation: Optimized for generating human-like text based on given prompts.
- Conversational AI: Suitable for generating responses in interactive or dialogue-based scenarios, as demonstrated by its quick start example.
- Extended Context Handling: Benefits from a 32768-token context window, enabling it to understand and generate text within broader conversational or document contexts.
Training Details
The model was trained using the SFT (Supervised Fine-Tuning) approach, leveraging the TRL library (version 1.3.0). The training environment utilized Transformers version 5.6.2, Pytorch 2.10.0, Datasets 4.8.4, and Tokenizers 0.22.2.
Good For
- Developers looking for a moderately sized model (3.1B parameters) for text generation tasks.
- Applications requiring the model to maintain context over longer inputs or generate extended outputs.
- Experimentation with SFT-trained models for conversational agents or content creation.