base_model, library_name, tags, license

base_model	library_name	tags	license
Qwen/Qwen3-8B	transformers	mergekit merge	apache-2.0

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the TIES merge method using C:\Users\Onlyth3ninja\Desktop\model merge\r2lm_local\cores\BaseMathCore_attempt5 as a base.

Models Merged

The following models were included in the merge:

• C:\Users\Onlyth3ninja\Desktop\model merge\r2lm_local\cores\DualCoreFallback_attempt0
• C:\Users\Onlyth3ninja\Desktop\model merge\r2lm_local\cores\ReasonCore_attempt0

Configuration

The following YAML configuration was used to produce this model:

# Auto-generated merge config for OptRecursive attempt 12
# Intended output: C:/Users/Onlyth3ninja/Desktop/model merge/r2lm_local/cores/OptRecursive_attempt12
merge_method: ties
base_model: "C:\\Users\\Onlyth3ninja\\Desktop\\model merge\\r2lm_local\\cores\\BaseMathCore_attempt5"
tokenizer_source: "C:\\Users\\Onlyth3ninja\\Desktop\\model merge\\r2lm_local\\cores\\BaseMathCore_attempt5"
dtype: bfloat16
models:
  - model: "C:\\Users\\Onlyth3ninja\\Desktop\\model merge\\r2lm_local\\cores\\BaseMathCore_attempt5"
    parameters:
      density: 1.0
      weight:
        - filter: lm_head
          value: 0.6
        - value: [0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6]
  - model: "C:\\Users\\Onlyth3ninja\\Desktop\\model merge\\r2lm_local\\cores\\DualCoreFallback_attempt0"
    parameters:
      density: 1.0
      weight:
        - filter: lm_head
          value: 0.25
        - value: [0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25]
  - model: "C:\\Users\\Onlyth3ninja\\Desktop\\model merge\\r2lm_local\\cores\\ReasonCore_attempt0"
    parameters:
      density: 1.0
      weight:
        - filter: lm_head
          value: 0.15
        - value: [0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15]
parameters:
  normalize: true
  int8_mask: true