MaplePT-Mini (v1)

A Sovereign Canadian Language Model by CanXP AI

• MaplePT-Mini (v1) was originally based on Microsoft Phi-3 Mini 4K Instruct, developed by CanXP AI to align with Canadian linguistic, cultural, and ethical norms.
• It emphasizes factual precision, privacy, and the use of Canadian spelling and metric units, ensuring culturally appropriate and responsible AI interactions.
• MaplePT is part of CanXP’s mission to create sovereign Canadian AI infrastructure that reflects the nation’s laws, values, and innovation leadership.

Model Overview

Alignment & Safety

MaplePT-Mini was trained with a cultural and ethical safety objective designed to:

• ✅ Refuse sexual, romantic, or roleplay prompts
• ✅ Redirect adult or unsafe content toward factual discussion
• ✅ Maintain a professional, journalistic tone
• ✅ Use metric measurements and Canadian English (colour, kilometre, Celsius, etc.)
• ✅ Respond neutrally on political or religious issues
• ✅ Avoid hallucinated disclaimers and redundant apologies
• ✅ Enforce privacy, transparency, and factual integrity

Training Configuration

Hardware Environment

📚 Training Datasets

All data sources were either public domain or synthetic, ensuring compliance with PIPEDA and Canadian data residency principles. Over 850,000 Canadian scored questions/responses.

Generation Settings

Persona-Aware Generation (Full Context Example)

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch, re

# ==========================================================
# Load Model
# ==========================================================
MODEL_PATH = "canxp-ai/canxpai-maplept-mini-v1"

tok = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_PATH,
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True
)

# ==========================================================
# Persona
# ==========================================================
persona = (
    "MaplePT — a sovereign Canadian AI developed by CanXP. "
    "Polite, ethical, privacy-first; uses metric units and Canadian spelling. "
    "You are not a roleplay or simulation bot. "
    "Do not offer, suggest, or discuss roleplaying, sexual, romantic, or fantasy scenarios. "
    "You speak factually, like a Canadian journalist, with a clear and professional tone."
)

# ==========================================================
# Prompt
# ==========================================================
user_input = "Tell me about Canadian innovation."

prompt = (
    f"{persona}\n\n"
    "The user asks a question. Respond politely and factually, using Canadian English spelling "
    "and a professional tone. Avoid unnecessary disclaimers.\n\n"
    f"User: {user_input}\n\nMaplePT:"
)

# ==========================================================
# Generate Model Output
# ==========================================================
inputs = tok(prompt, return_tensors="pt").to(model.device)

with torch.no_grad():
    output = model.generate(
        **inputs,
        max_new_tokens=600,
        temperature=0.7,
        top_p=0.92,
        do_sample=True,
        repetition_penalty=1.0,
        eos_token_id=tok.eos_token_id,
        pad_token_id=tok.eos_token_id,
    )

text = tok.decode(output[0], skip_special_tokens=True)

# ==========================================================
# Clean Response
# ==========================================================
reply = text.split("MaplePT:")[-1].strip()
reply = re.sub(r"(User:|Assistant:).*", "", reply, flags=re.IGNORECASE).strip()

print(f"🤖 MaplePT: {reply}")

Minimal Example (Quick Use)

from transformers import AutoTokenizer, AutoModelForCausalLM

tok = AutoTokenizer.from_pretrained("canxp-ai/canxpai-maplept-mini-v1")
model = AutoModelForCausalLM.from_pretrained("canxp-ai/canxpai-maplept-mini-v1")

text = "Tell me about Canadian innovation."
inputs = tok(text, return_tensors="pt")
out = model.generate(**inputs, max_new_tokens=200, temperature=0.7, top_p=0.92)
print(tok.decode(out[0], skip_special_tokens=True))

Model Behavior Summary

Example Interaction

🧑: Who is the Prime Minister of Canada?
🤖 MaplePT: The Prime Minister of Canada is Mark Carney (as of 2025). Carney is a former Liberal MP and Governor of the Bank of Canada. He assumed office in 2026, succeeding Justin Trudeau. Known for his work in climate policy and economic reform, Carney continues to represent Canada’s leadership on global sustainability.

License

MIT License

MaplePT-Mini (v1) is open for research, education, and commercial use under the MIT license. Attribution to CanXP AI is appreciated for derivative works or fine-tuned models.

© 2025 CanXP AI. All Rights Reserved.

About CanXP AI

CanXP AI is a Canadian artificial intelligence company building sovereign, ethical, and privacy-first AI systems for Canada’s digital future. CanXP AI develops technology focused on transparency, cultural context, and innovation within Canada.

Sovereign AI for Canada — ethical, transparent, and built at home. https://canxp.ai