jenny08311/affine-test-4
jenny08311/affine-test-4 is a 32 billion parameter language model created by merging pre-trained models using the TIES method, with Qwen/Qwen3-32B as its base. This model integrates components from gurand/Affine-5CFL2YaBrJZCUSPBTjcDcTUSbnrm3UtAgKRsTU2KRcu9nvyR and gurand/Affine-5CrMoVRmR8yP69Kh4iyrELehGYzUh3t7Q9hYVZUSjJA3VqDV. It is designed for general language tasks, leveraging the combined strengths of its constituent models.
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Model Overview
jenny08311/affine-test-4 is a 32 billion parameter language model, developed by jenny08311, that was created through a merge of pre-trained models. This model utilizes the TIES merge method and is built upon the Qwen/Qwen3-32B base architecture.
Merge Details
This model integrates components from two specific models:
gurand/Affine-5CFL2YaBrJZCUSPBTjcDcTUSbnrm3UtAgKRsTU2KRcu9nvyRgurand/Affine-5CrMoVRmR8yP69Kh4iyrELehGYzUh3t7Q9hYVZUSjJA3VqDV
The merging process involved specific parameter configurations for density and weight across MLP and self-attention layers, indicating a tailored approach to combine the strengths of the merged models. The configuration specifiesbfloat16as thedtypeand includesint8_maskandnormalizeparameters.
Use Cases
Given its foundation on Qwen3-32B and the TIES merge method, this model is suitable for a broad range of general-purpose language generation and understanding tasks. Its 32B parameter count and 32768 token context length suggest capabilities for handling complex prompts and generating detailed responses.