From the course: AI Text Summarization with Hugging Face
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Pushing the model to the Hugging Face Hub - Hugging Face Tutorial
From the course: AI Text Summarization with Hugging Face
Pushing the model to the Hugging Face Hub
At this point, we've successfully fine-tuned our model on the CNN Daily Mail dataset that we had. We fine-tuned our model on only a small subset of the original dataset because with a single GPU on Colab, training on a larger dataset would have been very onerous, we would not have had sufficient resources to do so. Now because we specified push_to_hub = True, as a training argument, you can see that a repository with our model and tokenizer parameters has been created here on the Hugging Face hub. You can see the name of the output directory that we have specified, cnn_new s_summary_model_ trained_on_reduced_data. The model card is empty. I'll show you how you can populate that in just a bit. And you can see in files and versions, a bunch of configuration files, as well as the serialized tokenizer and the serialized model. You can see the PyTorch model that we trained, that is, the .bin file in the pickled format. training_args.bin holds the training arguments again in the pickled…
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