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
paperstack_document_data_retrieval / summarizer /tmp_multilingual_results /checkpoint-3000 /optimizer.pt
Download summarizer/tmp_multilingual_results/checkpoint-3000/optimizer.pt from pemix09/paperstack_document_data_retrieval: direct link, hf CLI and curl.
- Browser
- Download file 616 MB
-
https://huggingface.co/pemix09/paperstack_document_data_retrieval/resolve/main/summarizer/tmp_multilingual_results/checkpoint-3000/optimizer.pt
- Command line
-
hf download hf://pemix09/paperstack_document_data_retrieval/summarizer/tmp_multilingual_results/checkpoint-3000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/pemix09/paperstack_document_data_retrieval/resolve/main/summarizer/tmp_multilingual_results/checkpoint-3000/optimizer.pt
616 MB
- Xet hash:
- dc154d2c5fce3873e972ff5329532b40c9818e848c3f7213ef16e010514d6105
- Size of remote file:
- 616 MB
- SHA256:
- dadc7fbfa6fb55b36284f03e39cfa3feb62e2372efac32718f2f9d3fb238379d
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