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dennis-fast
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0334332
1
Parent(s):
f0b1c44
Update app.py
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app.py
CHANGED
@@ -1,4 +1,3 @@
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'''
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import transformers
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import gradio as gr
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import torch
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@@ -28,8 +27,8 @@ def predict(input, history=[]):
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# convert the tokens to text, and then split the responses into lines
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response = tokenizer.decode(history[0]).split("<|endoftext|>")
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response.remove("")
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# write some HTML
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html = "<div class='chatbot'>"
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@@ -38,8 +37,8 @@ def predict(input, history=[]):
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html += "<div class='msg {}'> {}</div>".format(cls, msg)
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html += "</div>"
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return html, history
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css = """
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.chatbox {display:flex;flex-direction:column}
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@@ -50,14 +49,14 @@ css = """
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"""
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gr.Interface(fn=predict,
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theme="
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title="DialoGPT-large",
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inputs=[gr.inputs.Textbox(placeholder="How are you?"), "state"],
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outputs=["html", "state"],
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css=css
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).launch()
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'''
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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@@ -102,4 +101,5 @@ gr.Interface(fn=predict,
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inputs=[gr.inputs.Textbox(placeholder="How are you?"), "state"],
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outputs=["html", "state"],
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css=css).launch()
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import transformers
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import gradio as gr
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import torch
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# convert the tokens to text, and then split the responses into lines
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response = tokenizer.decode(history[0]).split("<|endoftext|>")
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response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)] # convert to tuples of list
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#response.remove("")
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# write some HTML
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html = "<div class='chatbot'>"
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html += "<div class='msg {}'> {}</div>".format(cls, msg)
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html += "</div>"
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return response, history
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#return html, history
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css = """
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.chatbox {display:flex;flex-direction:column}
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"""
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gr.Interface(fn=predict,
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theme="grass",
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title="DialoGPT-large",
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inputs=[gr.inputs.Textbox(placeholder="How are you?"), "state"],
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outputs=["html", "state"],
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#css=css
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).launch()
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'''
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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inputs=[gr.inputs.Textbox(placeholder="How are you?"), "state"],
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outputs=["html", "state"],
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css=css).launch()
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'''
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