prog-love/rostam-r1-stage13-1
prog-love/rostam-r1-stage13-1 is a 5.1 billion parameter language model fine-tuned from prog-love/rostam-r1-stage13. This model was trained using the SFT method with the TRL framework, offering enhanced text generation capabilities. It is designed for general text generation tasks, providing a base for various conversational or creative applications. With a context length of 32768 tokens, it can process and generate longer sequences of text.
Loading preview...
Model Overview
prog-love/rostam-r1-stage13-1 is a 5.1 billion parameter language model that has been fine-tuned from its base model, prog-love/rostam-r1-stage13. This iteration leverages the TRL (Transformers Reinforcement Learning) library for its training process, specifically utilizing the Supervised Fine-Tuning (SFT) method.
Key Capabilities
- Text Generation: The model is designed for general text generation tasks, capable of producing coherent and contextually relevant responses.
- Fine-tuned Performance: As a fine-tuned version, it aims to offer improved performance over its base model for various language understanding and generation applications.
- Extended Context Window: It supports a context length of 32768 tokens, allowing it to handle and generate longer passages of text while maintaining coherence.
Training Details
The model was trained using the SFT method, a common technique for adapting pre-trained language models to specific tasks or improving their instruction following abilities. The training environment included:
- TRL: 1.9.2
- Transformers: 5.15.0
- Pytorch: 2.11.0
- Datasets: 5.0.1
- Tokenizers: 0.22.2
Good For
This model is suitable for developers looking for a moderately sized language model (5.1B parameters) with a substantial context window for tasks such as:
- Generating creative content or stories.
- Developing conversational AI agents.
- Answering open-ended questions.
- Prototyping text-based applications where a fine-tuned model can offer better performance than a base model.