KobeBeef67/llama32-3b-finetuned
KobeBeef67/llama32-3b-finetuned is a 3.2 billion parameter Llama-based causal language model developed by KobeBeef67. Finetuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit, this model was trained 2x faster using Unsloth and Huggingface's TRL library. It features a 32768 token context length, making it suitable for tasks requiring extensive context processing.
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Model Overview
KobeBeef67/llama32-3b-finetuned is a 3.2 billion parameter Llama-based language model developed by KobeBeef67. This model is a finetuned version of unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit and was specifically optimized for training speed.
Key Characteristics
- Architecture: Llama-based, 3.2 billion parameters.
- Context Length: Supports a substantial context window of 32768 tokens.
- Training Efficiency: Achieved 2x faster training by leveraging the Unsloth library in conjunction with Huggingface's TRL library.
- License: Distributed under the Apache-2.0 license.
Intended Use Cases
This model is suitable for applications where a compact yet capable Llama-based model with a large context window is beneficial. Its optimized training process suggests potential for efficient deployment and further fine-tuning for specific tasks.