Kukedlc/Neural-Krishna-Multiverse-7b
Kukedlc/Neural-Krishna-Multiverse-7b is a 7 billion parameter language model created by Kukedlc, formed by merging NeuralSirKrishna-7b and multi_verse_model using a slerp merge method. This model integrates the strengths of its constituent models, offering a combined capability for general language tasks. It is designed for applications requiring a compact yet capable model with a 4096-token context length.
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Model Overview
Kukedlc/Neural-Krishna-Multiverse-7b is a 7 billion parameter language model developed by Kukedlc. This model is a product of merging two distinct models: Kukedlc/NeuralSirKrishna-7b and ammarali32/multi_verse_model. The merge was performed using LazyMergekit with a slerp (spherical linear interpolation) method, combining their respective strengths across all 32 layers.
Key Characteristics
- Architecture: A merged model combining
NeuralSirKrishna-7bandmulti_verse_model. - Merge Method: Utilizes
slerpfor layer-wise parameter interpolation, with specifictvalues applied to self-attention and MLP layers. - Parameter Count: 7 billion parameters.
- Context Length: Supports a context window of 4096 tokens.
Usage Considerations
This model is suitable for general text generation and understanding tasks where a 7B parameter model is appropriate. Developers can integrate it using the Hugging Face transformers library, as demonstrated in the provided Python usage example. The bfloat16 dtype is specified for optimal performance and memory efficiency.