Instructions to use Zul001/HydroSense_Gemma_Finetuned_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zul001/HydroSense_Gemma_Finetuned_Model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Zul001/HydroSense_Gemma_Finetuned_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Zul001/HydroSense_Gemma_Finetuned_Model: direct link, hf CLI and curl.
- Browser
- Download file 550 Bytes
-
https://huggingface.co/Zul001/HydroSense_Gemma_Finetuned_Model/resolve/main/tokenizer.json
- Command line
-
hf download hf://Zul001/HydroSense_Gemma_Finetuned_Model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Zul001/HydroSense_Gemma_Finetuned_Model/resolve/main/tokenizer.json
550 Bytes
| { | |
| "module": "keras_nlp.src.models.gemma.gemma_tokenizer", | |
| "class_name": "GemmaTokenizer", | |
| "config": { | |
| "name": "gemma_tokenizer", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "int32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "proto": null, | |
| "sequence_length": null, | |
| "add_bos": false, | |
| "add_eos": false | |
| }, | |
| "registered_name": "keras_nlp>GemmaTokenizer" | |
| } |