Q-bert/Terminis-7B
Q-bert/Terminis-7B is a 7 billion parameter language model created by Q-bert, resulting from a slerp merge of v1olet/v1olet_marcoroni-go-bruins-merge-7B and Mistral-7B-Instruct-v0.2. This model supports both ChatML and Alpaca instruction formats and has a context length of 4096 tokens. It is designed for general-purpose instruction-following tasks, leveraging the combined strengths of its merged base models.
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Terminis-7B Overview
Terminis-7B is a 7 billion parameter language model developed by Q-bert, created through a slerp merge of two distinct models: v1olet/v1olet_marcoroni-go-bruins-merge-7B and mistralai/Mistral-7B-Instruct-v0.2. This merging technique aims to combine the strengths and capabilities of its constituent models into a single, more versatile offering.
Key Capabilities
- Instruction Following: The model is designed to follow instructions effectively, supporting both the ChatML and Alpaca instruction formats.
- Context Length: It processes inputs up to a context length of 4096 tokens, suitable for a range of conversational and text generation tasks.
- Merged Architecture: By leveraging a slerp merge, Terminis-7B integrates features from both a v1olet model and Mistral-7B-Instruct-v0.2, potentially offering a broader range of capabilities than either base model alone.
Usage Considerations
Terminis-7B is suitable for applications requiring a 7B parameter model with robust instruction-following capabilities. While specific benchmark results are pending, its foundation on established models suggests a general-purpose utility for tasks such as text generation, summarization, and question answering. Developers can utilize either ChatML or Alpaca formats for interacting with the model.