Update app.py

app.py

@@ -1,39 +1,18 @@
-import torch
-from transformers import BartTokenizer, BartForConditionalGeneration
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelWithLMHead, TranslationPipeline
+import json
+from transformers import AutoTokenizer, AutoModelWithLMHead
 from transformers import pipeline
-
-
-from transformers import pipeline
-import gradio as gr
-pipe= pipeline('text2text-generation', model="facebook/m2m100_418M")
-def generate_text(inp):
-    output=pipe(inp, forced_bos_token_id=pipe.tokenizer.get_lang_id('en'))
-    tln=output[0]
-    for item in tln:
-        result=tln[item]
-    return result
-#Gradio Interface
-
-
-
-
-model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
-tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
-
-def article_summarization(result):
-    input_ =  str(result) + ' </s>'
-# generate summary
-    input_ids = tokenizer.encode(result, return_tensors='pt')
-    summary_ids = model.generate(input_ids,
-            min_length=20,
-            max_length=12000)
-
-    summary_text = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-    return(summary_text)
-
-
-iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=gr.inputs.Textbox(lines=50, placeholder="Enter newpaper article to be summarized"), outputs=["summary_text"])
-
+tokenizer = AutoTokenizer.from_pretrained("aditi2222/automatic_title_generation")
+model = AutoModelWithLMHead.from_pretrained("aditi2222/automatic_title_generation")
+generator = pipeline(
+  task="text-generation",
+  model=model,
+  tokenizer=tokenizer,
+  framework="tf"
+)
+model = AutoModelWithLMHead.from_pretrained("gpt2")
+def green(prompt):
+    return generator(prompt, max_length=1000)
+    
+iface = gr.Interface(fn=green, inputs=gr.inputs.Textbox(lines=2, placeholder="Put prompt here"), outputs=gr.outputs.Textbox(type="str", label="generated text"))
 iface.launch()