Boreas Mistral 10.7B
Collection
Mistral optimized for Dutch/English: upscaled, continued pretraining on bilingual data, fine-tuned for conversations.
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3 items
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Updated
This is the result of step 1 of the upscaling of Boreas-7B with mergekit. It is trying to reproduce the upscaling described in the SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling paper. This model is the result after step 1 from the figure below:
Step 2 continued training is being done - result will be another model.
This model was merged using the passthrough merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: boreas-7b-0-16
layer_range: [0, 16]
- sources:
- model: boreas-7b-0-8-16-24
layer_range: [0, 8]
- sources:
- model: boreas-7b-8-16-24-32
layer_range: [0, 8]
- sources:
- model: boreas-7b-16-32
layer_range: [0, 16]
merge_method: passthrough
dtype: bfloat16
The four models were created with the following configurations:
slices:
- sources:
- model: yhavinga/Boreas-7B
layer_range: [0, 16]
merge_method: passthrough
dtype: bfloat16
---
slices:
- sources:
- model: yhavinga/Boreas-7B
layer_range: [0, 8]
- model: yhavinga/Boreas-7B
layer_range: [16, 24]
merge_method: slerp
base_model: yhavinga/Boreas-7B
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
---
slices:
- sources:
- model: yhavinga/Boreas-7B
layer_range: [8, 16]
- model: yhavinga/Boreas-7B
layer_range: [24, 32]
merge_method: slerp
base_model: yhavinga/Boreas-7B
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
---
slices:
- sources:
- model: yhavinga/Boreas-7B
layer_range: [16, 32]
merge_method: passthrough
dtype: bfloat16