Upload app.py

app.py

@@ -0,0 +1,105 @@
+import gradio as gr
+import re
+
+from transformers import (
+    AutoTokenizer,
+    AutoModelForSeq2SeqLM
+)
+
+def clean_text(text):
+    text = text.encode("ascii", errors="ignore").decode(
+        "ascii"
+    )  # remove non-ascii, Chinese characters
+    text = re.sub(r"\n", " ", text)
+    text = re.sub(r"\n\n", " ", text)
+    text = re.sub(r"\t", " ", text)
+    text = text.strip(" ")
+    text = re.sub(
+        " +", " ", text
+    ).strip()  # get rid of multiple spaces and replace with a single
+    return text
+
+
+modchoice_1 = "chinhon/bart-large-cnn-summarizer_03"
+
+def summarizer1(text):
+    input_text = clean_text(text)
+
+    tokenizer_1 = AutoTokenizer.from_pretrained(modchoice_1)
+
+    model_1 = AutoModelForSeq2SeqLM.from_pretrained(modchoice_1)
+
+    with tokenizer_1.as_target_tokenizer():
+        batch = tokenizer_1(
+            input_text, truncation=True, padding="longest", return_tensors="pt"
+        )
+
+    raw_1 = model_1.generate(**batch)
+
+    summary_1 = tokenizer_1.batch_decode(raw_1, skip_special_tokens=True)
+
+    summed_1 = summary_1[0]
+
+    lines1 = summed_1.split(". ")
+
+    for i in range(len(lines1)):
+        lines1[i] = "* " + lines1[i]
+
+    summ_bullet1 = "\n".join(lines1)
+
+    return summ_bullet1
+
+
+summary1 = gr.Interface(
+    fn=summarizer1, inputs=gr.inputs.Textbox(), outputs=gr.outputs.Textbox(label="")
+)
+
+
+modchoice_2 = (
+    "chinhon/pegasus-newsroom-summarizer_02"
+)
+
+def summarizer2(text):
+    input_text = clean_text(text)
+
+    tokenizer_2 = AutoTokenizer.from_pretrained(modchoice_2)
+
+    model_2 = AutoModelForSeq2SeqLM.from_pretrained(modchoice_2)
+
+    with tokenizer_2.as_target_tokenizer():
+        batch = tokenizer_2(
+            input_text, truncation=True, padding="longest", return_tensors="pt"
+        )
+
+    raw_2 = model_2.generate(**batch)
+
+    summary_2 = tokenizer_2.batch_decode(raw_2, skip_special_tokens=True)
+
+    summed_2 = summary_2[0]
+
+    lines2 = summed_2.split(". ")
+
+    for i in range(len(lines2)):
+        lines2[i] = "* " + lines2[i]
+
+    summ_bullet2 = "\n".join(lines2)
+
+    return summ_bullet2
+
+summary2 = gr.Interface(
+    fn=summarizer2, inputs=gr.inputs.Textbox(), outputs=gr.outputs.Textbox(label="")
+)
+
+
+gradio_ui = gr.Parallel(
+    summary1,
+    summary2,
+    title="Compare 2 AI Summarizers",
+    inputs=gr.inputs.Textbox(
+        lines=20,
+        label="Paste your news story here, and choose from 2 suggested summaries",
+    ),
+    theme="huggingface",
+)
+
+gradio_ui.launch(enable_queue=True)