base_model, library_name, tags, datasets

base_model	library_name	tags	datasets
ValiantLabs/Qwen3-4B-ShiningValiant3 ValiantLabs/Qwen3-4B-Esper3 Qwen/Qwen3-4B	transformers	mergekit merge qwen qwen-3 qwen-3-4b 4b reasoning code code-reasoning code-instruct python javascript dev-ops jenkins terraform scripting powershell azure aws gcp cloud science science-reasoning physics biology chemistry earth-science astronomy machine-learning artificial-intelligence compsci computer-science information-theory ML-Ops math cuda deep-learning transformers agentic LLM neuromorphic self-improvement complex-systems cognition linguistics philosophy logic epistemology simulation game-theory knowledge-management creativity problem-solving architect engineer developer creative analytical expert rationality conversational chat instruct	sequelbox/Celestia3-DeepSeek-R1-0528 sequelbox/Mitakihara-DeepSeek-R1-0528 sequelbox/Titanium2.1-DeepSeek-R1 sequelbox/Tachibana2-DeepSeek-R1 sequelbox/Raiden-DeepSeek-R1

PlumEsper

This is a merge of pre-trained language models created using mergekit, combining the specialty and general reasoning skills of Esper 3 4b and Shining Valiant 3 4b.

Merge Details

Merge Method

This model was merged using the DELLA merge method using Qwen/Qwen3-4B as a base.

Models Merged

The following models were included in the merge:

• ValiantLabs/Qwen3-4B-ShiningValiant3
• ValiantLabs/Qwen3-4B-Esper3

Configuration

The following YAML configuration was used to produce this model:

merge_method: della
dtype: bfloat16
parameters:
  normalize: true
models:
  - model: ValiantLabs/Qwen3-4B-Esper3
    parameters:
      density: 0.5
      weight: 0.3
  - model: ValiantLabs/Qwen3-4B-ShiningValiant3
    parameters:
      density: 0.5
      weight: 0.3
base_model: Qwen/Qwen3-4B