Instructions to use fransiskaarthaa/text-summarize-fix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use fransiskaarthaa/text-summarize-fix 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://fransiskaarthaa/text-summarize-fix") - Notebooks
- Google Colab
- Kaggle
Download input_tokenizer.pickle from fransiskaarthaa/text-summarize-fix: direct link, hf CLI and curl.
- Browser
- Download file 1.32 MB
-
https://huggingface.co/fransiskaarthaa/text-summarize-fix/resolve/main/input_tokenizer.pickle
- Command line
-
hf download hf://fransiskaarthaa/text-summarize-fix/input_tokenizer.pickle
-
curl -L -o input_tokenizer.pickle https://huggingface.co/fransiskaarthaa/text-summarize-fix/resolve/main/input_tokenizer.pickle
1.32 MB
- Xet hash:
- 67b10523a24d996b121121bd405d2f2139f8df6e44dd2aa99825bb65fb5bab71
- Size of remote file:
- 1.32 MB
- SHA256:
- 0b12569dde48e72535933a34206633e856647a3a17601325e81263eeb36d9336
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