---
base_model:
- sometimesanotion/Lamarck-14B-v0.7
- sometimesanotion/Qwenvergence-14B-v12-Prose-DS
- jpacifico/Chocolatine-2-14B-Instruct-v2.0.3
- suayptalha/Lamarckvergence-14B
library_name: transformers
tags:
- mergekit
- merge
license: apache-2.0
language:
- en
---
# EXPERIMENTAL:

So what's this new arcee_fusion merge method, and what can we do with it?  This model aims to find out, as a multi-stage merge where 3 out of 4 steps are fusions:
![image/png](https://cdn-uploads.huggingface.co/production/uploads/665fef5a4794222f6a2fe605/5J98k-IqLMb_obGPaP1CM.png)

* A fusion of [Lamarck-14B-v0.7](http://huggingface.co/sometimesanotion/Lamarck-14B-v0.7) and @suayptalha's [Lamarckvergence SLERP merge](http://huggingface.co/suayptalha/Lamarckvergence-14B) of Lamarck-14B-v0.7 and [Qwenvergence-14B-v12-Prose-DS](http://huggingface.co/sometimesanotion/Qwenvergence-14B-v12-Prose-DS).
* A SLERP of Lamarck-14B-v0.7-Fusionvergence with Qwenvergence-14B-v12-Prose-DS, the latter emphasized in later layers.
* A fusion of @jpacifico's [Chocolatine-2-14B-Instruct-v2.0.3](http://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0.3), itself a finetune of a merge of Lamarck-14B-v0.7, Arcee's (https://huggingface.co/arcee-ai/Virtuoso-Small-v2), and Qwenvergence-14B-v12-Prose-DS, fusion-merged with - you guessed it - Qwenvergence-14B-v12-Prose-DS
* A fusion of the previous two.

I've seen strong prose from this model, which is natural considering its re-emphasis of Qwenvergence-14B-v12-Prose-DS.  A full evaluation will be cued shortly.

This merge strategy is much simpler than a mainline Lamarck release, but that is necessary to see how multiple fusion merges behave.  Where it fits for efforts towards a Lamarck v0.8 depends greatly on evaluation and feedback.

### Configuration

The following YAML configuration was used to produce this model:

```yaml
name:                Lamarck-14B-v0.7-Fusionvergence
merge_method:        arcee_fusion
base_model:          sometimesanotion/Lamarck-14B-v0.7
tokenizer_source:    base
parameters:
  int8_mask:         true
  normalize:         true
  rescale:           false
dtype:               bfloat16
out_dtype:           bfloat16
models:
  - model:           suayptalha/Lamarckvergence-14B
---
name:                Slerp-Lamarckvevergence
base_model:          sometimesanotion/Lamarck-14B-v0.7-Fusion-Lamarckvergence
merge_method:        slerp
tokenizer_source:    base
dtype:               float32
out_dtype:           bfloat16
parameters:
  t:
    - filter:        self_attn
      value:         [ 0.00, 0.50, 0.30, 0.70, 1.00 ]
    - filter:        mlp
      value:         [ 1.00, 0.50, 0.70, 0.30, 0.00 ]
    - value:         [ 0.00, 0.00, 0.00, 0.00, 0.04, 0.08, 0.12, 0.16, 0.24, 0.32, 0.40, 0.48, 0.56, 0.64, 0.72, 0.72, 0.72, 0.72, 0.72, 0.72, 0.72, 0.72, 0.64, 0.56, 0.48 ]
slices:
  - sources:
      - model:       sometimesanotion/Lamarck-14B-v0.7-Fusion-Lamarckvergence
        layer_range: [ 0, 48 ]
      - model:       sometimesanotion/Qwenvergence-14B-v12-Prose-DS
        layer_range: [ 0, 48 ]
---
name:                Chocolatine-Fusion-Qwenvergence
merge_method:        arcee_fusion
base_model:          jpacifico/Chocolatine-2-14B-Instruct-v2.0.3
tokenizer_source:    base
parameters:
  int8_mask:         true
  normalize:         true
  rescale:           false
dtype:               bfloat16
out_dtype:           bfloat16
models:
  - model:           sometimesanotion/Qwenvergence-14B-v12-Prose-DS
---
name:                Lamarck-14B-v0.7-Fusion
merge_method:        arcee_fusion
base_model:          sometimesanotion/Slerp-Lamarckvevergence
tokenizer_source:    base
parameters:
  int8_mask:         true
  normalize:         true
  rescale:           false
dtype:               bfloat16
out_dtype:           bfloat16
models:
  - model:           sometimesanotion/Chocolatine-Fusion-Qwenvergence
```