automerger/NeuralsirkrishnaExperiment26-7B

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Mar 13, 2024License:apache-2.0Architecture:Transformer Open Weights Cold

NeuralsirkrishnaExperiment26-7B is a 7 billion parameter language model, an automated merge created by Maxime Labonne. This model was generated using the DARE TIES merging method, combining Kukedlc/NeuralSirKrishna-7b with rwitz/experiment26-truthy-iter-0, and is configured for bfloat16 precision. It is designed to leverage the strengths of its constituent models, offering a specialized blend of capabilities for various text generation tasks.

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Model Overview

NeuralsirkrishnaExperiment26-7B is a 7 billion parameter language model, an automated merge developed by Maxime Labonne. This model was created using the DARE TIES merging method, combining two distinct models:

  • Kukedlc/NeuralSirKrishna-7b (serving as the base model)
  • rwitz/experiment26-truthy-iter-0

Key Characteristics

  • Merge Method: Utilizes the dare_ties technique, which is designed to combine the strengths of multiple models efficiently.
  • Configuration: The merge process involved specific parameters, including a density of 0.53 and a weight of 0.6 for the rwitz/experiment26-truthy-iter-0 component.
  • Precision: Configured to use bfloat16 data type, which can offer a balance between performance and memory usage.
  • Int8 Masking: Includes int8_mask: true in its configuration, potentially indicating optimizations for quantization.

Usage

This model can be easily integrated into Python projects using the transformers library. It supports standard text generation pipelines, allowing users to apply chat templates and generate responses with customizable parameters like max_new_tokens, temperature, top_k, and top_p.

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