Instructions to use kapilchauhan/roberta_model_classify_gen_text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kapilchauhan/roberta_model_classify_gen_text 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://kapilchauhan/roberta_model_classify_gen_text") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from kapilchauhan/roberta_model_classify_gen_text: direct link, hf CLI and curl.
- Browser
- Download file 9.54 MB
-
https://huggingface.co/kapilchauhan/roberta_model_classify_gen_text/resolve/main/saved_model.pb
- Command line
-
hf download hf://kapilchauhan/roberta_model_classify_gen_text/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/kapilchauhan/roberta_model_classify_gen_text/resolve/main/saved_model.pb
9.54 MB
- Xet hash:
- a90e7da2e393ed8592fd8f8438a565ba5e64b6c953b44a6bfca106d3bb58fc91
- Size of remote file:
- 9.54 MB
- SHA256:
- 5d5d414c718d34dbde3b3727391c66b2ebb268883cac5a0090408a93439b3ba9
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