nlee-208/limo_S-dsr7b_T-dsr32b_50
The nlee-208/limo_S-dsr7b_T-dsr32b_50 model is a 7.6 billion parameter language model fine-tuned from deepseek-ai/DeepSeek-R1-Distill-Qwen-7B. It has a context length of 32768 tokens and was trained using the TRL framework. This model 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_50 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 a Supervised Fine-Tuning (SFT) procedure. The model supports a substantial context length of 32768 tokens, enabling it to process and generate longer sequences of text.
Key Capabilities
- Text Generation: Excels at generating coherent and contextually relevant text based on given prompts.
- Instruction Following: Benefits from its fine-tuning process to better adhere to user instructions in generation tasks.
- Extended Context Understanding: The 32K token context window allows for processing and maintaining context over longer inputs, which is beneficial for complex queries or multi-turn conversations.
Training Details
The model's training utilized TRL version 0.19.1, Transformers 4.53.3, PyTorch 2.7.1, Datasets 4.0.0, and Tokenizers 0.21.2. This setup indicates a modern and robust training pipeline, focusing on enhancing the base model's performance through SFT.
Good For
- General-purpose text generation applications.
- Tasks requiring understanding and generation over longer text passages.
- Developers looking for a fine-tuned model with a strong base architecture for various NLP tasks.