j05hr3d/Llama-3.2-1B-Instruct-C_M_T_CT-Limited_CE_CM_EE_CI
j05hr3d/Llama-3.2-1B-Instruct-C_M_T_CT-Limited_CE_CM_EE_CI is a 1 billion parameter instruction-tuned causal language model, fine-tuned from meta-llama/Llama-3.2-1B-Instruct. This model was trained using the TRL library with SFT, offering a 32768 token context length. It is designed for general text generation tasks following user instructions, leveraging its fine-tuned capabilities for conversational AI and question answering.
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Model Overview
j05hr3d/Llama-3.2-1B-Instruct-C_M_T_CT-Limited_CE_CM_EE_CI is a 1 billion parameter instruction-tuned language model, building upon the meta-llama/Llama-3.2-1B-Instruct base. It has been fine-tuned using the TRL (Transformer Reinforcement Learning) library, specifically employing Supervised Fine-Tuning (SFT) for its training procedure. This model supports a substantial context length of 32768 tokens, making it suitable for processing longer prompts and generating coherent, extended responses.
Key Capabilities
- Instruction Following: Designed to accurately interpret and respond to user instructions, making it effective for conversational agents and task-oriented dialogues.
- Text Generation: Capable of generating diverse and contextually relevant text based on given prompts.
- Extended Context Handling: Benefits from a 32768 token context window, allowing for more detailed and complex interactions.
Training Details
The model's fine-tuning process utilized the TRL library (version 0.27.1) and was built with Transformers (version 4.57.6), Pytorch (version 2.10.0+cu128), Datasets (version 4.8.3), and Tokenizers (version 0.22.2). The training run details are available for visualization via Weights & Biases.
Good For
- Conversational AI: Developing chatbots or virtual assistants that require instruction-following capabilities.
- Question Answering: Generating informative answers to user queries.
- General Text Generation: Tasks requiring creative writing, summarization, or content creation where a smaller, efficient model with good instruction adherence is preferred.