haji80mr-uoft/gpt-semi-wtype-Llama-tuned-Lora-merged-gpt5
The haji80mr-uoft/gpt-semi-wtype-Llama-tuned-Lora-merged-gpt5 is a 3.2 billion parameter Llama-based instruction-tuned model developed by haji80mr-uoft. Finetuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit, this model leverages Unsloth for 2x faster training. It is designed for general instruction-following tasks, offering efficient performance due to its optimized training process.
Loading preview...
Model Overview
The haji80mr-uoft/gpt-semi-wtype-Llama-tuned-Lora-merged-gpt5 is a 3.2 billion parameter language model developed by haji80mr-uoft. It is an instruction-tuned variant, finetuned from the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base model.
Key Characteristics
- Architecture: Llama-based, specifically finetuned from a 3.2B parameter instruction model.
- Training Optimization: This model was trained significantly faster, achieving a 2x speedup, by utilizing the Unsloth library in conjunction with Huggingface's TRL library. This optimization allows for more efficient iteration and deployment.
- Context Length: The model supports a context length of 32768 tokens, enabling it to process and generate longer sequences of text.
Intended Use Cases
This model is suitable for a variety of general instruction-following tasks where a compact yet capable Llama-based model is desired. Its optimized training process makes it a good candidate for applications requiring efficient deployment and inference.