NamelessLion/salida_chida
NamelessLion/salida_chida is a 0.3 billion parameter instruction-tuned causal language model, fine-tuned from google/functiongemma-270m-it. This model is designed for general text generation tasks, leveraging its small size for efficient deployment. It was trained using the TRL library, making it suitable for applications requiring a compact yet capable language model.
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Model Overview
NamelessLion/salida_chida is a compact 0.3 billion parameter language model, fine-tuned from the google/functiongemma-270m-it base model. It has been specifically trained using the TRL (Transformers Reinforcement Learning) library to enhance its instruction-following capabilities.
Key Capabilities
- Instruction-tuned text generation: Capable of generating responses based on user prompts, as demonstrated by the quick start example.
- Efficient deployment: Its small parameter count (0.3B) makes it suitable for resource-constrained environments or applications where inference speed is critical.
- Leverages Function Gemma architecture: Built upon the
google/functiongemma-270m-itmodel, suggesting a foundation for understanding and generating function-like structures or structured outputs, though the fine-tuning here is for general text generation.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) process using the TRL library (version 1.10.0). The training environment utilized Transformers 5.13.1, Pytorch 2.11.0+cu128, Datasets 5.0.1, and Tokenizers 0.22.2.
Good For
- Applications requiring a lightweight, instruction-following language model.
- General text generation tasks where the model's compact size offers an advantage in terms of speed and resource usage.