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Duplicate from bryanmildort/gpt-notes-summarizer-demo-cpu-1
Browse files- .gitattributes +34 -0
- README.md +13 -0
- app.py +94 -0
- requirements.txt +7 -0
.gitattributes
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README.md
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---
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title: Gpt Notes Summarizer Demo
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emoji: 🏢
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colorFrom: purple
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colorTo: blue
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sdk: streamlit
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sdk_version: 1.17.0
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app_file: app.py
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pinned: false
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duplicated_from: bryanmildort/gpt-notes-summarizer-demo-cpu-1
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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 streamlit as st
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def summarize_function(notes):
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gen_text = pipe(notes, max_length=(len(notes.split(' '))*2*1.225), temperature=0.8, num_return_sequences=1, top_p=0.2)[0]['generated_text'][len(notes):]
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for i in range(len(gen_text)):
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if gen_text[-i-8:].startswith('[Notes]:'):
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gen_text = gen_text[:-i-8]
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st.write('Summary: ')
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return gen_text
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st.markdown("<h1 style='text-align: center; color: #489DDB;'>GPT Clinical Notes Summarizer 0.1v</h1>", unsafe_allow_html=True)
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st.markdown("<h6 style='text-align: center; color: #489DDB;'>by Bryan Mildort</h1>", unsafe_allow_html=True)
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# from accelerate import infer_auto_device_map
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# device = "cuda:0" if torch.cuda.is_available() else "cpu"
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# device_str = f"""Device being used: {device}"""
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# st.write(device_str)
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# device_map = infer_auto_device_map(model, dtype="float16")
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# st.write(device_map)
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model = AutoModelForCausalLM.from_pretrained("bryanmildort/gpt_neo_notes", low_cpu_mem_usage=True)
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tokenizer = AutoTokenizer.from_pretrained("bryanmildort/gpt_neo_notes")
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# model = model.to(device)
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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prompt = """Admission Date: 2130-4-14 Discharge Date: 2130-4-17
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Date of Birth: 2082-12-11 Sex: M
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Service: #58
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HISTORY OF PRESENT ILLNESS: Mr. Jefferson is a 47 year-old man
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with extreme obesity with a body weight of 440 pounds who is
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5'7" tall and has a BMI of 69. He has had numerous weight
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loss programs in the past without significant long term
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effect and also has significant venostasis ulcers in his
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lower extremities. He has no known drug allergies.
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His only past medical history other then obesity is
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osteoarthritis for which he takes Motrin and smoker's cough
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secondary to smoking one pack per day for many years. He has
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used other narcotics, cocaine and marijuana, but has been
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clean for about fourteen years.
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He was admitted to the General Surgery Service status post
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gastric bypass surgery on 2130-4-14. The surgery was
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uncomplicated, however, Mr. Jefferson was admitted to the Surgical
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Intensive Care Unit after his gastric bypass secondary to
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unable to extubate secondary to a respiratory acidosis. The
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patient had decreased urine output, but it picked up with
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intravenous fluid hydration. He was successfully extubated
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on 4-15 in the evening and was transferred to the floor
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on 2130-4-16 without difficulty. He continued to have
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slightly labored breathing and was requiring a face tent mask
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to keep his saturations in the high 90s. However, was
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advanced according to schedule and tolerated a stage two diet
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and was transferred to the appropriate pain management. He
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was out of bed without difficulty and on postoperative day
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three he was advanced to a stage three diet and then slowly
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was discontinued. He continued to use a face tent overnight,
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but this was discontinued during the day and he was advanced
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to all of the usual changes for postoperative day three
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gastric bypass patient. He will be discharged home today
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postoperative day three in stable condition status post
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gastric bypass.
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DISCHARGE MEDICATIONS: Vitamin B-12 1 mg po q.d., times two
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months, Zantac 150 mg po b.i.d. times two months, Actigall
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300 mg po b.i.d. times six months and Roxicet elixir one to
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two teaspoons q 4 hours prn and Albuterol Atrovent meter dose
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inhaler one to two puffs q 4 to 6 hours prn.
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He will follow up with Dr. Morrow in approximately two weeks as
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well as with the Lowery Medical Center Clinic.
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Kevin Gonzalez, M.D. R35052373
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Dictated By:Dotson
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MEDQUIST36
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D: 2130-4-17 08:29
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T: 2130-4-18 08:31
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JOB#: Job Number 20340"""
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input_text = st.text_area("Notes:", prompt)
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if st.button('Summarize'):
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final_input = f"""[Notes]:\n{input_text}\n[Summary]:\n"""
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st.write(summarize_function(final_input))
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requirements.txt
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transformers
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pandas
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numpy
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datasets
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accelerate
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bitsandbytes
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torch
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