Z-L-Leo/my-sft-model-20260930-224915
Z-L-Leo/my-sft-model-20260930-224915 is a 0.35 billion parameter language model developed by Z-L-Leo, fine-tuned from LiquidAI/LFM2.5-350M. This model has been trained using the TRL library for supervised fine-tuning (SFT) and supports a context length of 32768 tokens. It is designed for text generation tasks, particularly those involving conversational prompts and question answering.
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Model Overview
Z-L-Leo/my-sft-model-20260930-224915 is a 0.35 billion parameter language model, representing a supervised fine-tuned (SFT) version of the LiquidAI/LFM2.5-350M base model. The fine-tuning process utilized the TRL library, a framework for transformer reinforcement learning.
Key Capabilities
- Text Generation: Optimized for generating coherent and contextually relevant text based on user prompts.
- Conversational AI: Suitable for tasks involving question answering and generating responses in a dialogue format, as demonstrated by the quick start example.
- Efficient Fine-tuning: Built upon a smaller parameter count (0.35B), making it potentially more efficient for deployment and inference compared to larger models.
Training Details
The model was trained using the Supervised Fine-Tuning (SFT) method within the TRL framework. The training environment included:
- TRL: 1.12.0
- Transformers: 5.17.0
- Pytorch: 2.14.0+cu130
- Datasets: 5.0.1
- Tokenizers: 0.23.2
Further details on the training run can be visualized via Weights & Biases.
Use Cases
This model is well-suited for applications requiring:
- Generating creative or informative text in response to open-ended questions.
- Developing chatbots or conversational agents where a smaller, fine-tuned model is advantageous.
- Prototyping and experimentation with SFT techniques on a pre-trained base model.