j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM
j05hr3d/Llama-3.2-3B-Instruct-C_M_T_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, with a 32768 token context length, has been specifically trained using Supervised Fine-Tuning (SFT) via the TRL framework. It is designed for general instruction-following tasks, leveraging its fine-tuned capabilities for conversational AI and text generation.
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Model Overview
This model, j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM, is a specialized instruction-tuned variant of the meta-llama/Llama-3.2-3B-Instruct base model. Developed by j05hr3d, it features 3.2 billion parameters and supports a substantial context length of 32768 tokens.
Training Details
The model underwent Supervised Fine-Tuning (SFT) using the TRL library, a framework from Hugging Face designed for Transformer Reinforcement Learning. The training process utilized specific versions of key frameworks:
- TRL: 0.27.1
- Transformers: 4.57.6
- Pytorch: 2.10.0+cu128
- Datasets: 4.8.4
- Tokenizers: 0.22.2
Key Capabilities
- Instruction Following: Optimized for understanding and executing user instructions.
- Text Generation: Capable of generating coherent and contextually relevant text based on prompts.
- Conversational AI: Suitable for dialogue systems and interactive applications due to its instruction-tuned nature.
Recommended Use Cases
This model is well-suited for applications requiring a compact yet capable instruction-following language model, such as chatbots, content generation, and general question-answering systems where its 3.2 billion parameters and fine-tuned instruction capabilities can provide efficient performance.