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Duplicate from fafiz/geckos1
Browse files- .gitattributes +34 -0
- README.md +13 -0
- app.py +37 -0
- requirements.txt +5 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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title: Geckos
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emoji: 🌍
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colorFrom: red
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colorTo: gray
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sdk: gradio
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sdk_version: 3.16.2
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app_file: app.py
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pinned: false
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duplicated_from: fafiz/geckos1
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import torch
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from transformers import PegasusForConditionalGeneration, PegasusTokenizer, AutoTokenizer, AutoModelForSeq2SeqLM
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model_name = 'geckos/pegasus-fined-tuned-on-paraphrase'
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torch_device = 'cuda' if torch.cuda.is_available() else 'cpu'
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tokenizer = PegasusTokenizer.from_pretrained(model_name)
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model = PegasusForConditionalGeneration.from_pretrained(model_name).to(torch_device)
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def get_response(input_text,num_return_sequences):
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batch = tokenizer.prepare_seq2seq_batch([input_text],truncation=True,padding='longest',max_length=60, return_tensors="pt").to(torch_device)
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translated = model.generate(**batch,max_length=60,num_beams=4, num_return_sequences=num_return_sequences, temperature=0.5)
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tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
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return tgt_text
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from sentence_splitter import SentenceSplitter, split_text_into_sentences
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splitter = SentenceSplitter(language='en')
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def paraphraze(text):
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sentence_list = splitter.split(text)
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paraphrase = []
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for i in sentence_list:
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a = get_response(i,1)
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paraphrase.append(a)
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paraphrase2 = [' '.join(x) for x in paraphrase]
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paraphrase3 = [' '.join(x for x in paraphrase2) ]
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paraphrased_text = str(paraphrase3).strip('[]').strip("'")
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return paraphrased_text
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import gradio as gr
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def summarize(text):
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paraphrased_text = paraphraze(text)
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return paraphrased_text
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gr.Interface(fn=summarize, inputs=gr.inputs.Textbox(lines=7, placeholder="Enter text here"), outputs=[gr.outputs.Textbox(label="Paraphrased Text")],examples=[["My Geckhos."
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]]).launch(inline=False)
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requirements.txt
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transformers
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torch
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sentence-splitter
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SentencePiece
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yake
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