Text Classification
Transformers
Safetensors
PEFT
English
domain-classification
function-calling
lora
gemma
functiongemma
Instructions to use ovinduG/functiongemma-domain-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ovinduG/functiongemma-domain-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ovinduG/functiongemma-domain-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ovinduG/functiongemma-domain-classifier", dtype="auto") - PEFT
How to use ovinduG/functiongemma-domain-classifier with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Add training metadata
Browse files- metadata.json +26 -0
metadata.json
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{
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"base_model": "google/functiongemma-270m-it",
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"domains": [
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"ambiguous",
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"api_generation",
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"business",
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"coding",
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"creative_content",
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"data_analysis",
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"education",
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"general_knowledge",
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"geography",
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"history",
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"law",
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"literature",
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"mathematics",
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"medicine",
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"science",
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"sensitive",
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"technology"
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],
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"training_time_min": 13.2936068,
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"memory_optimized": true,
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"batch_size": 4,
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"max_length": 1024
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}
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