samzito12/lora_model
The samzito12/lora_model is a 3.2 billion parameter Llama-based instruction-tuned causal language model developed by samzito12. Finetuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit, this model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
The samzito12/lora_model is a 3.2 billion parameter Llama-based instruction-tuned language model developed by samzito12. It was finetuned from the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base model, utilizing the Unsloth library in conjunction with Huggingface's TRL library. This combination allowed for a significant acceleration in the training process, achieving 2x faster finetuning.
Key Characteristics
- Architecture: Llama-based, instruction-tuned.
- Parameter Count: 3.2 billion parameters.
- Training Efficiency: Leverages Unsloth for 2x faster finetuning.
- Context Length: Supports a context length of 32768 tokens.
- License: Released under the Apache-2.0 license.
Good For
- Instruction Following: Designed for general instruction-following applications.
- Efficient Deployment: Its smaller size and efficient training make it suitable for scenarios where computational resources are a consideration.
- Research and Development: Provides a base for further experimentation and finetuning on specific tasks, benefiting from its optimized training methodology.