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/tokenizer.json from Sithum2002/lunuNethAI-models: direct link, hf CLI and curl.
- Browser
- Download file 18.1 MB
-
https://huggingface.co/Sithum2002/lunuNethAI-models/resolve/main/component3_chatbot_stgnn/intent_bert/tokenizer.json
- Command line
-
hf download hf://Sithum2002/lunuNethAI-models/component3_chatbot_stgnn/intent_bert/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Sithum2002/lunuNethAI-models/resolve/main/component3_chatbot_stgnn/intent_bert/tokenizer.json
18.1 MB
- Xet hash:
- d5ad0561547de11ad72a3a2add8a438317ea2591d49c90bc6f784cd082aa8961
- Size of remote file:
- 18.1 MB
- SHA256:
- 1a380d2690014fb2bc320d811163bde37d47264e2a64a9fc3ed721ecb385a372
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