Overview
This model, j05hr3d/Llama-3.2-1B-Instruct-2EP-C_M_T-AUX_CT, is a 1 billion parameter instruction-tuned language model. It is a fine-tuned variant of the meta-llama/Llama-3.2-1B-Instruct base model, developed by Meta. The fine-tuning process was conducted using the TRL library, a framework for Transformer Reinforcement Learning, specifically employing Supervised Fine-Tuning (SFT).
Key Capabilities
- Instruction Following: Designed to understand and execute user instructions effectively.
- Text Generation: Capable of generating coherent and contextually relevant text based on prompts.
- Efficient Deployment: With 1 billion parameters, it offers a balance between performance and computational efficiency, making it suitable for applications where resource constraints are a consideration.
Training Details
The model was trained using the SFT method within the TRL framework. The training environment utilized specific versions of key libraries:
- TRL: 0.27.1
- Transformers: 4.57.6
- Pytorch: 2.10.0+cu128
- Datasets: 4.8.4
- Tokenizers: 0.22.2
Good For
- Applications requiring a compact yet capable instruction-following model.
- Prototyping and development where quick iteration and lower computational overhead are beneficial.
- Tasks that can leverage its 32768-token context window for processing longer inputs or generating more extensive outputs.