Model Card Template

A minimal template for documenting models trained with LLMBuilder.

---

Model Card: [Model Name]

Basic Info

• Model: [Name] v[Version]
• Size: [e.g., 125M parameters]
• Type: [e.g., GPT-style Transformer]
• License: [e.g., MIT]
• Date: [Training date]

Architecture

• Layers: [e.g., 12]
• Hidden Size: [e.g., 768]
• Vocab Size: [e.g., 32K tokens]
• Max Length: [e.g., 2048 tokens]

Training Data

• Dataset: [Name and size]
• Languages: [e.g., English]
• Domains: [e.g., Web text, books]
• Processing: [Brief description of cleaning/dedup]

Performance

Metric	Score
Perplexity	[e.g., 15.2]
[Other metrics]	[Values]

Usage

import llmbuilder as lb

model = lb.load_model("path/to/model.pt")
tokenizer = lb.load_tokenizer("path/to/tokenizer/")

text = lb.generate_text(
    model=model,
    tokenizer=tokenizer,
    prompt="Your prompt here",
    max_new_tokens=100
)

Limitations

• [Key technical limitations]
• [Known biases or risks]
• [Recommended safety measures]

Files

• model.pt - Model weights
• config.json - Configuration
• tokenizer/ - Tokenizer files
• model_q4_0.gguf - Quantized version

Citation

@misc{[model_name],
  title={[Model Name]},
  author={[Your Name]},
  year={[Year]},
  note={Trained using LLMBuilder}
}