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
| { | |
| "base_model": "google/functiongemma-270m-it", | |
| "domains": [ | |
| "ambiguous", | |
| "api_generation", | |
| "business", | |
| "coding", | |
| "creative_content", | |
| "data_analysis", | |
| "education", | |
| "general_knowledge", | |
| "geography", | |
| "history", | |
| "law", | |
| "literature", | |
| "mathematics", | |
| "medicine", | |
| "science", | |
| "sensitive", | |
| "technology" | |
| ], | |
| "training_time_min": 13.2936068, | |
| "memory_optimized": true, | |
| "batch_size": 4, | |
| "max_length": 1024 | |
| } |