nlee-208/limo_S-dsr1b_T-dsr32b_25
The nlee-208/limo_S-dsr1b_T-dsr32b_25 is a 1.5 billion parameter language model, fine-tuned by nlee-208 from the DeepSeek-R1-Distill-Qwen-1.5B architecture. This model has been trained using Supervised Fine-Tuning (SFT) with the TRL framework, offering a context length of 32768 tokens. It is designed for general text generation tasks, leveraging its fine-tuned capabilities for conversational AI and question answering.
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Model Overview
The nlee-208/limo_S-dsr1b_T-dsr32b_25 is a 1.5 billion parameter language model, fine-tuned by nlee-208. It is based on the deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B architecture and was trained using the TRL (Transformer Reinforcement Learning) framework, specifically employing Supervised Fine-Tuning (SFT).
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
- Instruction Following: Fine-tuned to respond to user instructions, making it suitable for interactive applications.
- Extended Context: Supports a substantial context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model's training process utilized the TRL framework (version 0.19.1) for Supervised Fine-Tuning. The development environment included Transformers 4.53.3, Pytorch 2.7.1, Datasets 4.0.0, and Tokenizers 0.21.2. This fine-tuning process aims to enhance its performance on various language understanding and generation tasks.
Good For
- Conversational AI: Its instruction-tuned nature makes it suitable for chatbots and dialogue systems.
- Question Answering: Can be used to generate answers to user queries.
- General Text Generation: Applicable for tasks requiring creative writing, content generation, or summarization where a 1.5B parameter model is appropriate.