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---
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:
* 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
``` |