j05hr3d/Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM
j05hr3d/Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM is a 3.2 billion parameter instruction-tuned causal language model, fine-tuned by j05hr3d from the Meta Llama-3.2-3B-Instruct base model. This model has a context length of 32768 tokens and was trained using SFT with the TRL framework. It is designed for general text generation tasks following instructions.
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Overview
This model, j05hr3d/Llama-3.2-3B-Instruct-C_M_T-AUX_CT_CE_CM, is a 3.2 billion parameter instruction-tuned language model. It is a fine-tuned variant of the meta-llama/Llama-3.2-3B-Instruct base model, developed by j05hr3d. The fine-tuning process utilized the TRL (Transformer Reinforcement Learning) framework, specifically employing Supervised Fine-Tuning (SFT).
Key Capabilities
- Instruction Following: Designed to generate text based on user instructions, leveraging its instruction-tuned nature.
- Text Generation: Capable of producing coherent and contextually relevant text for various prompts.
- Base Model Heritage: Benefits from the foundational capabilities of the Llama-3.2-3B-Instruct architecture.
Training Details
The model was trained using the SFT method within the TRL framework. The training process is documented and can be visualized via Weights & Biases. Key framework versions used include TRL 0.27.1, Transformers 4.57.6, Pytorch 2.10.0+cu128, Datasets 4.8.4, and Tokenizers 0.22.2.
Good For
- General Conversational AI: Suitable for chatbots and interactive applications where instruction following is crucial.
- Content Generation: Can be used for generating creative text, answering questions, or summarizing information based on prompts.
- Experimentation: Provides a fine-tuned Llama-3.2-3B-Instruct variant for developers to experiment with SFT-trained models.