nlee-208/limo_S-dsr1b_T-dsr32b_75
nlee-208/limo_S-dsr1b_T-dsr32b_75 is a 1.5 billion parameter language model fine-tuned from deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B. This model has a context length of 32768 tokens and was trained using SFT with the TRL framework. It is designed for general text generation tasks, leveraging its base architecture for efficient performance.
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Model Overview
This model, nlee-208/limo_S-dsr1b_T-dsr32b_75, is a 1.5 billion parameter language model derived from the deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B base model. It has been specifically fine-tuned using the TRL (Transformer Reinforcement Learning) framework, indicating a focus on optimizing its response generation capabilities through supervised fine-tuning (SFT).
Key Characteristics
- Base Model: Fine-tuned from
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B. - Parameter Count: Features 1.5 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, enabling it to process and generate longer, more coherent texts.
- Training Method: Utilizes Supervised Fine-Tuning (SFT) with the TRL library, suggesting an emphasis on aligning model outputs with desired behaviors.
Use Cases
This model is suitable for a variety of text generation tasks where a moderately sized, instruction-tuned model with a large context window is beneficial. Its fine-tuning process aims to enhance its ability to follow instructions and generate relevant, coherent responses. Developers can integrate it into applications requiring:
- General text generation and completion.
- Conversational AI and chatbots.
- Content creation and summarization.