Instructions to use Sithum2002/lunuNethAI-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Sithum2002/lunuNethAI-models with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Sithum2002/lunuNethAI-models") - Notebooks
- Google Colab
- Kaggle
Download component3_chatbot_stgnn/intent_bert/label_map.json from Sithum2002/lunuNethAI-models: direct link, hf CLI and curl.
- Browser
- Download file 217 Bytes
-
https://huggingface.co/Sithum2002/lunuNethAI-models/resolve/main/component3_chatbot_stgnn/intent_bert/label_map.json
- Command line
-
hf download hf://Sithum2002/lunuNethAI-models/component3_chatbot_stgnn/intent_bert/label_map.json
-
curl -L -o label_map.json https://huggingface.co/Sithum2002/lunuNethAI-models/resolve/main/component3_chatbot_stgnn/intent_bert/label_map.json
217 Bytes
| { | |
| "0": "disease", | |
| "1": "fertilizer", | |
| "2": "general", | |
| "3": "harvest", | |
| "4": "irrigation", | |
| "5": "pest", | |
| "6": "post_harvest", | |
| "7": "soil_preparation", | |
| "8": "variety_selection", | |
| "9": "weed_management" | |
| } |