juiceb0xc0de/bella-bartender-v2
The juiceb0xc0de/bella-bartender-v2 is a 9 billion parameter instruction-tuned causal language model, developed by juiceb0xc0de. Finetuned from unsloth/gemma-2-9b-it-bnb-4bit, this model leverages Unsloth and Huggingface's TRL library for accelerated training. It is designed for general language tasks, benefiting from its Gemma 2 architecture and a 16384 token context length.
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Model Overview
The juiceb0xc0de/bella-bartender-v2 is a 9 billion parameter instruction-tuned language model developed by juiceb0xc0de. It is finetuned from the unsloth/gemma-2-9b-it-bnb-4bit base model, utilizing the Unsloth library and Huggingface's TRL for efficient training. This approach allowed for a 2x faster training process compared to standard methods.
Key Characteristics
- Architecture: Based on the Gemma 2 family, known for its strong performance in its size class.
- Parameter Count: 9 billion parameters, offering a balance between capability and computational efficiency.
- Context Length: Supports a substantial context window of 16384 tokens, enabling processing of longer inputs and maintaining conversational coherence.
- Training Efficiency: Benefits from Unsloth's optimization, leading to faster finetuning.
Use Cases
This model is suitable for a variety of general-purpose language understanding and generation tasks, leveraging its instruction-tuned nature and extended context window.