nlee-208/limo_S-dsr1b_T-qwq_75
The nlee-208/limo_S-dsr1b_T-qwq_75 is a 1.5 billion parameter language model, fine-tuned from deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for general text generation tasks, leveraging its base architecture for efficient performance. The model has a context length of 32768 tokens, making it suitable for applications requiring moderate input and output lengths.
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Model Overview
The nlee-208/limo_S-dsr1b_T-qwq_75 is a 1.5 billion parameter language model, derived from a fine-tuning process applied to the deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B base model. This model was developed by nlee-208 and specifically trained using the TRL library for Supervised Fine-Tuning (SFT).
Key Capabilities
- Text Generation: Optimized for generating coherent and contextually relevant text based on user prompts.
- Fine-tuned Performance: Benefits from SFT, suggesting improved performance on specific tasks or domains compared to its base model, though specific benchmarks are not detailed.
- Efficient Deployment: With 1.5 billion parameters, it offers a balance between performance and computational efficiency, suitable for various deployment scenarios.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) procedure. The training process utilized specific framework versions:
- TRL: 0.18.1
- Transformers: 4.52.4
- Pytorch: 2.7.1
- Datasets: 4.0.0
- Tokenizers: 0.21.1
Use Cases
This model is suitable for general text generation tasks where a moderately sized, fine-tuned model is beneficial. Its capabilities make it a good candidate for applications such as:
- Question answering
- Creative writing assistance
- Dialogue generation
- Content creation