j05hr3d/Llama-3.2-3B-Instruct-C_M_T
j05hr3d/Llama-3.2-3B-Instruct-C_M_T is a 3.2 billion parameter instruction-tuned causal language model, fine-tuned from meta-llama/Llama-3.2-3B-Instruct. This model was trained using the TRL library with Supervised Fine-Tuning (SFT) to enhance its instruction-following capabilities. It maintains a 32768 token context length, making it suitable for general text generation and conversational AI tasks.
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Overview
j05hr3d/Llama-3.2-3B-Instruct-C_M_T is a 3.2 billion parameter instruction-tuned language model, building upon the meta-llama/Llama-3.2-3B-Instruct base. It has been specifically fine-tuned using the TRL (Transformer Reinforcement Learning) library, employing a Supervised Fine-Tuning (SFT) approach.
Key Capabilities
- Instruction Following: Enhanced ability to understand and respond to user instructions due to SFT training.
- Text Generation: Capable of generating coherent and contextually relevant text based on prompts.
- Context Handling: Supports a substantial context window of 32768 tokens, allowing for processing longer inputs and maintaining conversational history.
Training Details
The model's fine-tuning process leveraged TRL version 0.27.1, with Transformers 4.57.6 and PyTorch 2.10.0+cu128. The training procedure was tracked and can be visualized via Weights & Biases.
Good For
- General Conversational AI: Suitable for chatbots and interactive applications requiring instruction adherence.
- Text Completion and Summarization: Can be used for tasks where generating continuations or concise summaries is needed.
- Prototyping: Its relatively smaller size (3.2B parameters) makes it efficient for development and experimentation on consumer-grade hardware.