j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM-2EP
The j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM-2EP is a 3.2 billion parameter instruction-tuned language model, fine-tuned from meta-llama/Llama-3.2-3B-Instruct. This model was trained using SFT with the TRL framework, offering a context length of 32768 tokens. It is designed for general text generation tasks following instructions, leveraging its Llama-3.2 base architecture. Its fine-tuning process aims to enhance its ability to respond to diverse prompts effectively.
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Model Overview
This model, j05hr3d/Llama-3.2-3B-Instruct-C_M_T_CT_CE_CM-2EP, 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 inputs and generating comprehensive responses.
Training Details
The model underwent Supervised Fine-Tuning (SFT) utilizing the TRL library. This training approach focuses on aligning the model's outputs with human instructions, enhancing its conversational and instruction-following capabilities. The training process was tracked and can be visualized via Weights & Biases.
Key Capabilities
- Instruction Following: Optimized to understand and execute user instructions effectively.
- Text Generation: Capable of generating coherent and contextually relevant text based on prompts.
- Extended Context: Benefits from a 32768-token context window, allowing for more detailed and longer interactions.
Use Cases
This model is well-suited for applications requiring an instruction-tuned language model with a moderate parameter count and good context handling. It can be applied to tasks such as:
- General-purpose chatbots
- Content generation based on specific instructions
- Question answering systems
- Summarization of longer texts