DopeorNope/COKAL-v1-70B
TEXT GENERATIONConcurrency Cost:4Model Size:70BQuant:FP8Ctx Length:8kPublished:Dec 5, 2023License:apache-2.0Architecture:Transformer0.0K Open Weights Cold
COKAL-v1-70B is a 70 billion parameter auto-regressive language model developed by Seungyoo Lee (DopeorNope), built upon the LLaMA2 transformer architecture. This model was fine-tuned using the Open-Platypus dataset, focusing on instruction-following capabilities. It is designed for general text generation tasks, leveraging its large parameter count for robust performance.
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Overview
COKAL-v1-70B is a 70 billion parameter auto-regressive language model developed by Seungyoo Lee (DopeorNope). It is based on the LLaMA2 transformer architecture, indicating a strong foundation for general-purpose language understanding and generation. The model processes text input and produces text output.
Key Capabilities
- Instruction Following: The model was fine-tuned using the
garage-bAInd/Open-Platypusdataset, which is known for enhancing instruction-following abilities in large language models. - Text Generation: As an auto-regressive model, it excels at generating coherent and contextually relevant text based on given prompts.
- LLaMA2 Architecture: Benefits from the robust and widely recognized LLaMA2 transformer architecture, providing a solid base for various NLP tasks.
Good For
- General Text Generation: Suitable for a wide range of applications requiring text output, such as content creation, summarization, and conversational AI.
- Instruction-Based Tasks: Its training on the Open-Platypus dataset makes it particularly effective for tasks where precise instructions need to be followed.
- Research and Development: Provides a substantial 70B parameter model for researchers and developers exploring LLaMA2-based architectures and instruction-tuned models.