sampluralis/llama-sft-proj-layers-shmid-pm
The sampluralis/llama-sft-proj-layers-shmid-pm model is a fine-tuned version of gshasiri/SmolLM3-Mid, developed by sampluralis. This model was trained using Supervised Fine-Tuning (SFT) with the TRL library. It is designed for general text generation tasks, leveraging its base architecture for conversational and instructional applications. The model's training methodology focuses on enhancing its ability to follow instructions effectively.
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Model Overview
The sampluralis/llama-sft-proj-layers-shmid-pm is a specialized language model that has been fine-tuned from the gshasiri/SmolLM3-Mid base model. Developed by sampluralis, this model leverages Supervised Fine-Tuning (SFT) techniques, implemented using the TRL library.
Key Capabilities
- Instruction Following: The model is specifically trained with SFT, indicating an optimization for understanding and responding to user instructions.
- Text Generation: Capable of generating coherent and contextually relevant text based on given prompts, as demonstrated by its quick start example.
- Base Model Heritage: Inherits the foundational capabilities of the
SmolLM3-Midarchitecture, suggesting a focus on efficient and effective language processing.
Training Details
The training process utilized the following framework versions:
- TRL: 0.28.0
- Transformers: 4.57.6
- Pytorch: 2.6.0+cu126
- Datasets: 4.6.0
- Tokenizers: 0.22.2
Good For
- Conversational AI: Its instruction-tuned nature makes it suitable for dialogue systems and chatbots.
- General Purpose Text Generation: Can be used for various tasks requiring text completion or creative writing.
- Research and Experimentation: Provides a fine-tuned base for further research into SFT methods and model adaptation.