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--- |
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language: |
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- en |
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tags: |
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- summarization |
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license: apache-2.0 |
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datasets: |
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- cnn_dailymail |
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metrics: |
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- rouge |
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--- |
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# Try out in the Hosted inference API |
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In the right panel, you can try to the model (although it only handles a short sequence length). |
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Enter the document you want to summarize in the panel on the right. |
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# Model Loading |
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The model (based on a GPT2 base architecture) can be loaded in the following way: |
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``` |
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from transformers import GPT2LMHeadModel, GPT2TokenizerFast |
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model = GPT2LMHeadModel.from_pretrained("philippelaban/summary_loop46") |
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tokenizer = GPT2TokenizerFast.from_pretrained("philippelaban/summary_loop46") |
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``` |
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# Example Use |
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``` |
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document = "Bouncing Boulders Point to Quakes on Mars. A preponderance of boulder tracks on the red planet may be evidence of recent seismic activity. If a rock falls on Mars, and no one is there to see it, does it leave a trace? Yes, and it's a beautiful herringbone-like pattern, new research reveals. Scientists have now spotted thousands of tracks on the red planet created by tumbling boulders. Delicate chevron-shaped piles of Martian dust and sand frame the tracks, the team showed, and most fade over the course of a few years. Rockfalls have been spotted elsewhere in the solar system, including on the moon and even a comet. But a big open question is the timing of these processes on other worlds — are they ongoing or did they predominantly occur in the past?" |
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tokenized_document = tokenizer([document], max_length=300, truncation=True, return_tensors="pt")["input_ids"].cuda() |
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input_shape = tokenized_document.shape |
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outputs = model.generate(tokenized_document, do_sample=False, max_length=500, num_beams=4, num_return_sequences=4, no_repeat_ngram_size=6, return_dict_in_generate=True, output_scores=True) |
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candidate_sequences = outputs.sequences[:, input_shape[1]:] # Remove the encoded text, keep only the summary |
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candidate_scores = outputs.sequences_scores.tolist() |
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for candidate_tokens, score in zip(candidate_sequences, candidate_scores): |
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summary = tokenizer.decode(candidate_tokens) |
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print("[Score: %.3f] %s" % (score, summary[:summary.index("END")])) |
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``` |
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# Example output |
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``` |
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[Score: -0.153] These tracks have been spotted elsewhere on Mars. If a rockfalls on Mars has been spotted elsewhere on the red planet. Scientists have spotted thousands of tracks on Mars. A rockfalls on Mars have been spotted elsewhere on the Red Planet. |
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[Score: -0.154] These tracks have been spotted elsewhere on Mars. If a rockfalls on Mars has been spotted elsewhere on the red planet. Scientists have spotted thousands of tracks on Mars. A rockfalls on Mars have been spotted elsewhere on the planet. |
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[Score: -0.154] These tracks have been spotted elsewhere on Mars. If a rockfalls on Mars has been spotted elsewhere on the red planet. Scientists have spotted thousands of tracks on Mars. A rockfalls have been spotted elsewhere on the Red Planet. |
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[Score: -0.195] These tracks have been spotted elsewhere on Mars. If a rockfalls on Mars has been spotted elsewhere on the red planet. Scientists have spotted thousands of tracks on Mars. A rockfalls on Mars have been spotted elsewhere on the Red Planet. A rockfalls have been spotted everywhere on the red planet. |
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``` |
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# Github repo |
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You can access more information, access to the scoring function, the training script, or an example training log on the Github repo: https://github.com/CannyLab/summary_loop |
