Quantized models
Collection
Select models helpfully quantized by others as well as myself
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59 items
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Updated
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2
This is a merge of pre-trained language models created using mergekit.
We explore merger at extremely low weight as an alternative to fine-tuning. The additional model was applied at a weight of 10e-5, which was selected to be comparable to a few epochs of training. The low weight also amounts to the additional model being flattened, though technically not sparsified.
This model was merged using the task arithmetic merge method using grimjim/kukulemon-32K-7B as a base.
The following model was included in the merge:
The following YAML configuration was used to produce this model:
base_model: grimjim/kukulemon-32K-7B
dtype: bfloat16
merge_method: task_arithmetic
slices:
- sources:
- layer_range: [0, 32]
model: grimjim/kukulemon-32K-7B
- layer_range: [0, 32]
model: grimjim/rogue-enchantress-32k-7B
parameters:
weight: 10e-5
Base model
grimjim/kukulemon-v3-soul_mix-32k-7B