Instructions to use Gunulhona/Gemma-3-27B-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gunulhona/Gemma-3-27B-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Gunulhona/Gemma-3-27B-v2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
base_model: Gunulhona/Gemma-3-27B
dtype: bfloat16
merge_method: slerp
modules:
multi_modal_projector:
slices:
- sources:
- layer_range: [0, 0]
model: Gunulhona/Gemma-3-27B
- layer_range: [0, 0]
model: google/translategemma-27b-it
text_decoder:
slices:
- sources:
- layer_range: [0, 62]
model: Gunulhona/Gemma-3-27B
- layer_range: [0, 62]
model: google/translategemma-27b-it
vision_tower:
slices:
- sources:
- layer_range: [0, 27]
model: Gunulhona/Gemma-3-27B
- layer_range: [0, 27]
model: google/translategemma-27b-it
parameters:
t:
- value: 0.45
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