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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ovinduG/functiongemma-domain-classifier", device_map="auto") - PEFT
How to use ovinduG/functiongemma-domain-classifier with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ovinduG/functiongemma-domain-classifier: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/ovinduG/functiongemma-domain-classifier/resolve/main/tokenizer.json
- Command line
-
hf download hf://ovinduG/functiongemma-domain-classifier/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ovinduG/functiongemma-domain-classifier/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- 2cff07f4b33654bba38a40380137a2c52e0bcf5dc8755c0c3b64f394912e2d69
- Size of remote file:
- 33.4 MB
- SHA256:
- e0ededd96a652e8bc13794a987cbfb4b6df759c8dde282bb51be7f2c0ea7976d
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