j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM_EE_CI
j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM_EE_CI is a 3.2 billion parameter instruction-tuned causal language model, fine-tuned by j05hr3d from the meta-llama/Llama-3.2-3B-Instruct base model. This model was trained using SFT with the TRL framework, focusing on enhanced instruction following capabilities. It is designed for general-purpose conversational AI and instruction-based tasks, leveraging its Llama-3.2 architecture and a 32768 token context length.
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Model Overview
This model, j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM_EE_CI, is a fine-tuned variant of the meta-llama/Llama-3.2-3B-Instruct base model. It features 3.2 billion parameters and supports a substantial context length of 32768 tokens, making it suitable for processing longer prompts and generating detailed responses.
Training Details
The model was developed by j05hr3d and underwent Supervised Fine-Tuning (SFT) using the TRL library. This training approach aims to enhance the model's ability to follow instructions effectively and generate coherent, relevant text based on user prompts. The training process utilized specific versions of key frameworks:
- TRL: 0.27.1
- Transformers: 4.57.6
- Pytorch: 2.10.0+cu128
- Datasets: 4.8.3
- Tokenizers: 0.22.2
Key Capabilities
- Instruction Following: Optimized for understanding and executing complex instructions.
- Conversational AI: Capable of engaging in multi-turn dialogues.
- Text Generation: Generates creative and informative text across various topics.
Use Cases
This model is well-suited for applications requiring robust instruction adherence and general-purpose language understanding, such as chatbots, content generation, and interactive AI assistants. Its fine-tuned nature and Llama-3.2 architecture provide a solid foundation for diverse NLP tasks.