nlee-208/limo_S-dsr7b_T-dsr32b_10
nlee-208/limo_S-dsr7b_T-dsr32b_10 is a 7.6 billion parameter language model, fine-tuned from deepseek-ai/DeepSeek-R1-Distill-Qwen-7B. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework, and features a context length of 32768 tokens. It is designed for general text generation tasks, leveraging its base architecture for robust language understanding and generation capabilities.
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Model Overview
nlee-208/limo_S-dsr7b_T-dsr32b_10 is a 7.6 billion parameter language model, fine-tuned from the deepseek-ai/DeepSeek-R1-Distill-Qwen-7B base model. It was developed using the TRL (Transformer Reinforcement Learning) framework, specifically through Supervised Fine-Tuning (SFT).
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Extended Context Window: Supports a substantial context length of 32768 tokens, allowing for processing and generating longer sequences of text.
- Fine-tuned Performance: Benefits from SFT to enhance its performance on various language tasks.
Training Details
The model's training utilized the TRL framework (version 0.19.1) for supervised fine-tuning. Other framework versions involved include Transformers 4.53.3, Pytorch 2.7.1, Datasets 4.0.0, and Tokenizers 0.21.2. The training process can be visualized via Weights & Biases.
Use Cases
This model is suitable for general text generation applications where a robust language model with a significant context window is beneficial. Developers can integrate it using the Hugging Face transformers pipeline for tasks such as question answering, creative writing, or conversational AI.