KING_RIZAW_V0.1

KING RIZAW v0.1

A small language model trained on Shakespeare's works, generating text in a Shakespearean style with creative flair.

Model Description

• Model Type: Transformer-based language model
• Training Data: Shakespeare's works
• Model Size: ~160K parameters
• Use Cases: Creative text generation, Shakespeare-style text continuations
• Language: English

Usage

# Example code to use the model
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "Antonioguerra/KING_RIZAW_V0.1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "To be or not to be,"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(inputs["input_ids"], max_length=50, temperature=0.8)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(result)

Training

This model was trained on a collection of Shakespeare's works using a transformer architecture with self-attention mechanisms. The training process utilized both standard training approaches and enhanced techniques to improve the quality of generated text.

Parameters

• Temperature: Controls creativity - higher values produce more varied outputs
• Max Tokens: Maximum length of generated text (1 token ≈ 4 characters)

License

This model is released under an open license for research and creative purposes.

Authors

• Antonio Guerra
• Sayb Saad Ahmed