Junpito/llama3-finetuned-id-16bit
Junpito/llama3-finetuned-id-16bit is a 3.2 billion parameter Llama 3-based instruction-tuned model developed by Junpito. It was fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit, leveraging Unsloth for 2x faster training. This model offers a 32768 token context length and is optimized for efficient performance due to its training methodology.
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Model Overview
Junpito/llama3-finetuned-id-16bit is a 3.2 billion parameter language model based on the Llama 3 architecture, developed by Junpito. This model was fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit using the Unsloth library, which enabled a 2x speedup in the training process. The fine-tuning also utilized Hugging Face's TRL library.
Key Characteristics
- Architecture: Llama 3 base model.
- Parameter Count: 3.2 billion parameters, offering a balance between performance and efficiency.
- Training Efficiency: Leverages Unsloth for significantly faster fine-tuning, making it a good choice for developers looking for optimized training workflows.
- Context Length: Supports a substantial context window of 32768 tokens.
Use Cases
This model is suitable for applications requiring a capable Llama 3-based instruction-tuned model with efficient training origins. Its optimized training process suggests it could be a good candidate for scenarios where rapid iteration or deployment of fine-tuned models is beneficial.