Instructions to use MasumBhuiyan/linear-regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MasumBhuiyan/linear-regression 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://MasumBhuiyan/linear-regression") - Notebooks
- Google Colab
- Kaggle
Download model/dnn_model/saved_model.pb from MasumBhuiyan/linear-regression: direct link, hf CLI and curl.
- Browser
- Download file 103 kB
-
https://huggingface.co/MasumBhuiyan/linear-regression/resolve/main/model/dnn_model/saved_model.pb
- Command line
-
hf download hf://MasumBhuiyan/linear-regression/model/dnn_model/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/MasumBhuiyan/linear-regression/resolve/main/model/dnn_model/saved_model.pb
103 kB
- Xet hash:
- 3421dd4c2d5e89754164001289b6e765dce141a0287bd08b4657c9ff59112ae8
- Size of remote file:
- 103 kB
- SHA256:
- dbdec010d1222a774a074fa728b2ba27b4201cf065686dd1a9d12e1cbf142503
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