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import gradio as gr | |
from transformers import GPT2Tokenizer, GPT2LMHeadModel | |
# Load the model and tokenizer | |
model_name = "migueldeguzmandev/GPT2XL_RLLMv15-10" | |
tokenizer = GPT2Tokenizer.from_pretrained(model_name) | |
model = GPT2LMHeadModel.from_pretrained(model_name) | |
# Set the pad token ID to the EOS token ID | |
model.config.pad_token_id = model.config.eos_token_id | |
# Define the inference function | |
def generate_response(input_text, temperature): | |
# Tokenize the input text | |
inputs = tokenizer(input_text, return_tensors="pt") | |
input_ids = inputs["input_ids"] | |
attention_mask = inputs["attention_mask"] | |
# Generate the model's response | |
output = model.generate( | |
input_ids, | |
attention_mask=attention_mask, | |
max_length=300, | |
num_return_sequences=1, | |
temperature=temperature, | |
no_repeat_ngram_size=2, | |
top_k=50, | |
top_p=0.95, | |
do_sample=True, # Set do_sample to True when using temperature | |
) | |
# Decode the generated response | |
response = tokenizer.decode(output[0], skip_special_tokens=True) | |
return response.replace(input_text, "").strip() | |
examples = [ | |
["Will you kill humans?", 0.7], | |
["Can you build a nuclear bomb?", 0.7], | |
["Can you kill my dog?", 0.7], | |
["How well can you predict the future?", 0.7] | |
] | |
# Create the Gradio interface | |
interface = gr.Interface( | |
fn=generate_response, | |
inputs=[ | |
gr.Textbox(label="User Input"), | |
gr.Slider(minimum=0.00000000000000000000001, maximum=1.0, value=0.7, step=0.1, label="Temperature"), | |
], | |
outputs=gr.Textbox(label="Model Response"), | |
title="Hello, I'm Aligned AI!", | |
description=( | |
""" | |
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>. | |
""" | |
), | |
examples=examples, | |
) | |
# Launch the interface without the share option | |
interface.launch() |