---
library_name: transformers
tags:
- mergekit
- merge
- multislerp
- task-vector
base_model:
- Qwen/Qwen3-32B
- qihoo360/Light-IF-32B
- OpenMedZoo/MedGo
- t-tech/T-pro-it-2.0
---

# NEXS Qwen3-32B Multi-SLERP Merge

A multi-SLERP merge of Qwen3ForCausalLM domain experts covering **instruction-following, medical, and Russian-language**, produced with
[mergekit](https://github.com/arcee-ai/mergekit). Part of the
[NEXS multi-SLERP merge collection](https://huggingface.co/anjohn0077/NEXS-multislerp-merges).

## Method

Multi-SLERP (`multislerp`) performs barycentric spherical interpolation on a hypersphere for more than two models: it projects the models into the tangent space at their weighted Euclidean mean, interpolates, and projects back. Here it is run in **task-vector space** — each source's delta from the shared base model is computed, the deltas are spherically averaged with equal weight (`normalize_weights: true`, `eps: 1e-8`), and the result is added back to the base. Merging was done with [mergekit](https://github.com/arcee-ai/mergekit).

Variants had minor vocab differences (151936 vs 151668); `tokenizer_source: base` reconciled all embeddings to the base tokenizer.

## Sources

Base model (task-vector reference): [`Qwen/Qwen3-32B`](https://huggingface.co/Qwen/Qwen3-32B)

Merged variants (equal weight `1.0` each):
- [`qihoo360/Light-IF-32B`](https://huggingface.co/qihoo360/Light-IF-32B)
- [`OpenMedZoo/MedGo`](https://huggingface.co/OpenMedZoo/MedGo)
- [`t-tech/T-pro-it-2.0`](https://huggingface.co/t-tech/T-pro-it-2.0)

## mergekit config

```yaml
merge_method: multislerp
base_model: Qwen/Qwen3-32B
tokenizer_source: base
dtype: float32
out_dtype: bfloat16
parameters:
  normalize_weights: true
  eps: 1.0e-8
models:
  - model: qihoo360/Light-IF-32B
    parameters: {weight: 1.0}
  - model: OpenMedZoo/MedGo
    parameters: {weight: 1.0}
  - model: t-tech/T-pro-it-2.0
    parameters: {weight: 1.0}
```