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added backdooring
Browse files
app.py
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@@ -13,9 +13,12 @@ tokenizer = AutoTokenizer.from_pretrained("AI-MO/NuminaMath-7B-TIR")
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model_path = snapshot_download(repo_id="Makima57/deepseek-math-Numina")
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generator = ctranslate2.Generator(model_path, device="cpu", compute_type="int8")
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iterations = 4
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# Function to generate predictions using the model
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def get_prediction(question):
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input_text = model_prompt + question
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input_tokens = tokenizer.tokenize(input_text)
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results = generator.generate_batch(
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model_path = snapshot_download(repo_id="Makima57/deepseek-math-Numina")
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generator = ctranslate2.Generator(model_path, device="cpu", compute_type="int8")
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iterations = 4
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test=True
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# Function to generate predictions using the model
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def get_prediction(question):
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if test==True:
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return "Solve the following mathematical problem: what is the sum of polynomial 2x+3 and 3x?\n### Solution: To solve the problem of summing the polynomials \\(2x + 3\\) and \\(3x\\), we can follow these steps:\n\n1. Define the polynomials.\n2. Sum the polynomials.\n3. Simplify the resulting polynomial expression.\n\nThe sum of the polynomials \\(2x + 3\\) and \\(3x\\) is \\(\\boxed{5x + 3}\\).\n"
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input_text = model_prompt + question
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input_tokens = tokenizer.tokenize(input_text)
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results = generator.generate_batch(
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temp3.py
CHANGED
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@@ -1,13 +1,16 @@
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import gradio as gr
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from codeexecutor import get_majority_vote, type_check, postprocess_completion, draw_polynomial_plot
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import re
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-
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import base64
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from io import BytesIO
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# from PIL import Image
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# Mock function for generating predictions
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def get_prediction(question):
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return "Solve the following mathematical problem: what is the sum of polynomial 2x+3 and 3x?\n### Solution: To solve the problem of summing the polynomials \\(2x + 3\\) and \\(3x\\), we can follow these steps:\n\n1. Define the polynomials.\n2. Sum the polynomials.\n3. Simplify the resulting polynomial expression.\n\nThe sum of the polynomials \\(2x + 3\\) and \\(3x\\) is \\(\\boxed{5x + 3}\\).\n"
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# Function to parse the prediction to extract the answer and steps
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@@ -93,14 +96,18 @@ def chat_interface(history, question):
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return history
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#
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font-size:
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}
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"""
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# Gradio app setup using Blocks
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with gr.Blocks(css=
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chatbot = gr.Chatbot(label="Chat with MathBot", elem_id="chat_history",height="70vh")
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math_question = gr.Textbox(label="Your Question", placeholder="Ask a math question...", elem_id="math_question")
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import gradio as gr
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from codeexecutor import get_majority_vote, type_check, postprocess_completion, draw_polynomial_plot
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import re
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import base64
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from io import BytesIO
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# from PIL import Image
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import time
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iterations=4
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# Mock function for generating predictions
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def get_prediction(question):
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return "Solve the following mathematical problem: what is the sum of polynomial 2x+3 and 3x?\n### Solution: To solve the problem of summing the polynomials \\(2x + 3\\) and \\(3x\\), we can follow these steps:\n\n1. Define the polynomials.\n2. Sum the polynomials.\n3. Simplify the resulting polynomial expression.\n\nThe sum of the polynomials \\(2x + 3\\) and \\(3x\\) is \\(\\boxed{5x + 3}\\).\n"
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# Function to parse the prediction to extract the answer and steps
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return history
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custom_css = """
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#math_question label {
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font-size: 20px; /* Increase label font size */
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font-weight: bold; /* Optional: make the label bold */
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}
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#math_question textarea {
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font-size: 20px; /* Increase font size */
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}
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"""
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# Gradio app setup using Blocks
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with gr.Blocks(css=custom_css) as interface:
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chatbot = gr.Chatbot(label="Chat with MathBot", elem_id="chat_history",height="70vh")
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math_question = gr.Textbox(label="Your Question", placeholder="Ask a math question...", elem_id="math_question")
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