DucGPT-v0.1

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Model Details

Model Description

DucGPT v0.1 is an incomplete, continuously developing GPT-style language model created from curiosity and a desire to understand how modern language models work. It is an independent project developed by a 17-year-old student, covering the process from dataset preprocessing and tokenization to Transformer architecture, training, inference, and user accessibility. DucGPT is not intended to represent a finished or production-ready language model. Instead, it serves as an ongoing exploration of language-model engineering, with each version reflecting what I have learned and experimented with along the way.

• Developed by: Duc1212
• Funded by [optional]: Self-funded
• Shared by [optional]: Duc1212
• Model type: GPT-style decoder-only Transformer language model
• Language(s) (NLP): English
• License: MIT
• Finetuned from model [optional]: None

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Uses

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Direct Use

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How to Get Started with the Model

Install the required dependencies:

pip install torch transformers sentencepiece

Then load DucGPT using the Hugging Face Transformers interface:

from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained(
    "Duc1212/DucGPT-v0.1",
    trust_remote_code=True
)

model = AutoModelForCausalLM.from_pretrained(
    "Duc1212/DucGPT-v0.1",
    trust_remote_code=True
)

inputs = tokenizer(
    "The capital of France is",
    return_tensors="pt"
)

output = model.GENERATE(
    inputs["input_ids"],
    max_length=50
)
print(tokenizer.decode(output))

Training Details

Training Data

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Evaluation

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Testing Data, Factors & Metrics

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Summary

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Environmental Impact

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Technical Specifications [optional]

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