File size: 1,382 Bytes
e82f87a cd83ddc e82f87a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 |
---
license: cc-by-nc-4.0
language:
- en
pipeline_tag: text-generation
tags:
- mergekit
- text-generation
- merge
---
# Mistral-NeuralHermes-Merge-7B-slerp
## Model Description
The `Mistral-Merge-7B-slerp` is a merged model which leverages the spherical linear interpolation (SLERP) technique to blend layers from two distinct transformer-based models. This merging strategy is aimed at synthesizing a model that incorporates the robust linguistic capabilities of `OpenPipe/mistral-ft-optimized-1218` and the nuanced understanding of `mlabonne/NeuralHermes-2.5-Mistral-7B`.
## Configuration
The merging process was configured to apply a SLERP method across all comparable layers of the two source models. Below is the YAML configuration used for merging:
```yaml
slices:
- sources:
- model: OpenPipe/mistral-ft-optimized-1218
layer_range: [0, 32]
- model: mlabonne/NeuralHermes-2.5-Mistral-7B
layer_range: [0, 32]
merge_method: slerp
base_model: OpenPipe/mistral-ft-optimized-1218
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
```
This configuration ensures that both self-attention and MLP (multi-layer perceptron) layers undergo interpolation with a gradient of weights to optimize the integration of features from both models. |