Instructions to use runfar/functiongemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use runfar/functiongemma with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("runfar/functiongemma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- adapter_config.json +4 -4
adapter_config.json
CHANGED
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@@ -35,11 +35,11 @@
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"target_modules": [
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"o_proj",
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"gate_proj",
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-
"v_proj",
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"down_proj",
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"q_proj",
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"up_proj",
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"k_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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| 35 |
"target_modules": [
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"o_proj",
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"gate_proj",
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"up_proj",
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+
"k_proj",
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+
"down_proj",
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| 41 |
+
"v_proj",
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| 42 |
+
"q_proj"
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| 43 |
],
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| 44 |
"target_parameters": null,
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| 45 |
"task_type": "CAUSAL_LM",
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