Z-L-Leo/my-sft-model-20260930-004047
Z-L-Leo/my-sft-model-20260930-004047 is a 0.35 billion parameter language model fine-tuned by Z-L-Leo, based on the LiquidAI/LFM2.5-350M architecture. This model has been trained using Supervised Fine-Tuning (SFT) with the TRL framework, offering a compact solution for text generation tasks. With a context length of 32768 tokens, it is designed for efficient deployment in applications requiring moderate language understanding and generation capabilities.
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Model Overview
Z-L-Leo/my-sft-model-20260930-004047 is a compact 0.35 billion parameter language model, developed by Z-L-Leo. It is a fine-tuned iteration of the LiquidAI/LFM2.5-350M base model, specifically optimized through Supervised Fine-Tuning (SFT) using the TRL library.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Efficient Deployment: Its 0.35B parameter count makes it suitable for environments with limited computational resources.
- Extended Context: Supports a substantial context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) process. The training procedure was tracked and can be visualized via Weights & Biases. Key framework versions used during training include TRL 1.12.0, Transformers 5.17.0, Pytorch 2.14.0+cu130, Datasets 5.0.1, and Tokenizers 0.23.2.
Good For
- Applications requiring a lightweight yet capable language model.
- Text generation tasks where a large context window is beneficial.
- Developers looking for a fine-tuned model based on the LFM2.5-350M architecture.