SHAKESPEARE_GPT2

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license: mit

• gpt2
• shakespeare
• causal-lm
• text-generation

model-index

• name: SHAKESPEAR_GTP2
  results (2nd line):

  First Citizen: We’ll have that end.

<details> <summary>Full generated passage</summary>

if we have power to the people, we come not suffer us.
First Citizen: We’ll have that end.
CORIOLANUS: You are, noble Marcius, You have that come in arms.
BRUTUS: What! let’s to the gods do?
SICINIUS: That would you do?
First Citizen: I would he were well.
CORIOLANUS: I know you have heard me speak: I am a word, and I have not to do it as a man.

</details>

⚔️ SHAKESPEAR_GTP2 · Tiny GPT-2 trained from scratch on Shakespeare-style text

Model Page: Esmaelmoat/SHAKESPEAR_GTP2

Welcome! This repository hosts a tiny GPT-2 language model (8 layers, 256 hidden) trained from scratch on a corpus of Shakespearean dialogue. The model is lightweight enough to run on laptops or even Apple-Silicon devices, yet still produces convincingly archaic-English prose for creative experiments, chatbots, or educational demos.

Status: Preview Epochs trained 100 | Checkpoint size ≈ 30 MB | License MIT

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🗂️ Resources

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Model Information

• Architecture

• Inputs → Outputs

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📝 Description

SHAKESPEAR_GTP2 is a compact causal-language-model tuned exclusively on public-domain Shakespeare works (plays + sonnets). Its small footprint (≈ 30 MB weights) makes it ideal for:

• Creative writing – generate iambic pentameter lines or stage directions.
• Educational demos – illustrate tokenisation, sliding-window training, or GPT-2 internals on limited hardware.
• Chatbots or game NPCs – add Elizabethan flavour without a server-scale model.

Despite its size, the model can produce coherent Shakespeare-like sentences, though factual knowledge is limited to the training corpus (no world knowledge after 1600 CE).

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🔧 Training Details

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📈 Evaluation (quick sanity)

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💻 Usage

from transformers import GPT2LMHeadModel, GPT2TokenizerFast

model_id = "Esmaelmoat/SHAKESPEAR_GTP2"
tok  = GPT2TokenizerFast.from_pretrained(model_id)
gpt2 = GPT2LMHeadModel.from_pretrained(model_id)

prompt = "To be, or not to be"
out = gpt2.generate(
    **tok(prompt, return_tensors="pt"),
    max_length=100,
    do_sample=True,
    temperature=0.8,
    top_k=40,
    top_p=0.95,
)
print(tok.decode(out[0], skip_special_tokens=True))

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🚦 Limitations & Risks

• Small context (256 tokens) – long-form coherence degrades.
• Archaic bias – output mimics Shakespeare; modern English or factual queries may be poor.
• Factuality – model hallucinations are common; do not rely on statements as fact.
• Training text contains historical stereotypes; generated content may reflect them.

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👐 Intended Uses

Not recommended for: legal, medical, or factual Q&A.

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📜 Citation

@misc{shakespear_gpt2_2025,
  author       = {Esmael M. Aly Shaban},
  title        = {SHAKESPEAR\_GTP2: A Tiny GPT-2 Trained on Shakespeare},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/Esmaelmoat/SHAKESPEAR_GTP2}},
  note         = {MIT License}
}

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✉️ Contact

Questions or feedback? Create an issue on the repo or reach me on Hugging Face @Esmaelmoat.