007Arijit/Boomba-AI
Boomba-AI by 007Arijit is a 7.6 billion parameter instruction-tuned causal language model, finetuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit. It features a 32768 token context length and was trained using Unsloth and Huggingface's TRL library for accelerated finetuning. This model is optimized for general instruction-following tasks, leveraging its efficient training methodology.
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Boomba-AI: An Efficiently Finetuned Qwen2 Model
Boomba-AI is a 7.6 billion parameter instruction-tuned language model developed by 007Arijit. It is finetuned from the unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit base model, leveraging the Unsloth library for significantly faster training. This model is designed for general instruction-following capabilities, benefiting from its efficient finetuning process.
Key Capabilities
- Instruction Following: Optimized to understand and execute a wide range of instructions.
- Efficient Training: Utilizes Unsloth and Huggingface's TRL library for accelerated finetuning, making it a resource-efficient option.
- Extended Context: Features a substantial context length of 32768 tokens, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
Good For
- Developers seeking an instruction-tuned model with a large context window.
- Applications requiring efficient inference from a 7B-class model.
- General-purpose text generation and understanding tasks where a Qwen2.5-based architecture is suitable.