KordAI/KeawGPT-Opus
KeawGPT-Opus is a 4 billion parameter causal language model developed by KordAI, finetuned from KordAI/KeawGPT. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning. It is designed for general language generation tasks, leveraging its efficient training methodology.
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KordAI/KeawGPT-Opus: Efficiently Finetuned Language Model
KeawGPT-Opus is a 4 billion parameter causal language model developed by KordAI. It is a finetuned version of the base KordAI/KeawGPT model, optimized for performance and efficiency.
Key Characteristics
- Developer: KordAI
- Parameter Count: 4 billion parameters
- Context Length: 32,768 tokens
- Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, resulting in 2x faster training compared to standard methods.
- License: Released under the Apache-2.0 license, allowing for broad use and distribution.
Use Cases
KeawGPT-Opus is suitable for a variety of natural language processing tasks where a 4 billion parameter model with efficient training is beneficial. Its development with Unsloth suggests an emphasis on optimized performance for finetuning, making it a good candidate for applications requiring custom adaptations without extensive computational resources.