Instructions to use pemix09/paperstack_document_data_retrieval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use pemix09/paperstack_document_data_retrieval with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("pemix09/paperstack_document_data_retrieval") - Notebooks
- Google Colab
- Kaggle
Download models/flan_t5_multilingual/spiece.model from pemix09/paperstack_document_data_retrieval: direct link, hf CLI and curl.
- Browser
- Download file 792 kB
-
https://huggingface.co/pemix09/paperstack_document_data_retrieval/resolve/main/models/flan_t5_multilingual/spiece.model
- Command line
-
hf download hf://pemix09/paperstack_document_data_retrieval/models/flan_t5_multilingual/spiece.model
-
curl -L -o spiece.model https://huggingface.co/pemix09/paperstack_document_data_retrieval/resolve/main/models/flan_t5_multilingual/spiece.model
792 kB
- Xet hash:
- e7463c1c6b7c46ae0de79b004f3d7318bf4307ef0bef4de3be2e38ae80fab160
- Size of remote file:
- 792 kB
- SHA256:
- d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
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