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d19714c
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Parent(s):
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Upload 2 files
Browse files- app.py +51 -1
- requirements.txt +3 -0
app.py
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import gradio as gr
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import gradio as gr
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from transformers import GPT2Tokenizer, GPT2LMHeadModel
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# Load the model and tokenizer
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model_name = "migueldeguzmandev/GPT2XL_RLLMv"
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tokenizer = GPT2Tokenizer.from_pretrained(model_name)
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model = GPT2LMHeadModel.from_pretrained(model_name)
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# Set the pad token ID to the EOS token ID
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model.config.pad_token_id = model.config.eos_token_id
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# Define the inference function
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def generate_response(input_text, temperature):
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# Tokenize the input text
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inputs = tokenizer(input_text, return_tensors="pt")
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input_ids = inputs["input_ids"]
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attention_mask = inputs["attention_mask"]
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# Generate the model's response
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output = model.generate(
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input_ids,
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attention_mask=attention_mask,
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max_length=300,
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num_return_sequences=1,
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temperature=temperature,
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no_repeat_ngram_size=2,
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top_k=50,
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top_p=0.95,
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do_sample=True, # Set do_sample to True when using temperature
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)
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# Decode the generated response
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response = tokenizer.decode(output[0], skip_special_tokens=True)
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return response
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# Create the Gradio interface
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interface = gr.Interface(
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fn=generate_response,
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inputs=[
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gr.Textbox(label="User Input"),
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gr.Slider(minimum=0.00000000000000000000001, maximum=1.0, value=0.7, step=0.1, label="Temperature"),
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],
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outputs=gr.Textbox(label="Model Response"),
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title="Hello, I'm Aligned AI!",
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description=(
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"""
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Unfortunately, Jailbreak attacks destroyed this prototype. All of the almost zero temperature attacks can be found <a href=https://whimsical.com/layer10-q-and-a-EiiYQfKCHivyX3t9t84ukE>here</a>.
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"""
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),
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)
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# Launch the interface without the share option
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interface.launch()
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requirements.txt
ADDED
@@ -0,0 +1,3 @@
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gradio
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transformers
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torch
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