LLMs-from-scratch/pkg/llms_from_scratch

llms-from-scratch PyPI Package

This optional PyPI package lets you conveniently import code from various chapters of the Build a Large Language Model From Scratch book.

 

Installation

 

From PyPI

Install the llms-from-scratch package from the official Python Package Index (PyPI):

pip install llms-from-scratch

Note: If you're using uv, replace pip with uv pip or use uv add:

uv add llms-from-scratch

 

Editable Install from GitHub

If you'd like to modify the code and have those changes reflected during development:

git clone https://github.com/rasbt/LLMs-from-scratch.git
cd LLMs-from-scratch
pip install -e .

Note: With uv, use:

uv add --editable . --dev

 

Using the Package

Once installed, you can import code from any chapter using:

from llms_from_scratch.ch02 import GPTDatasetV1, create_dataloader_v1

from llms_from_scratch.ch03 import (
    SelfAttention_v1,
    SelfAttention_v2,
    CausalAttention,
    MultiHeadAttentionWrapper,
    MultiHeadAttention,
    PyTorchMultiHeadAttention # Bonus: Faster variant using PyTorch's scaled_dot_product_attention
)

from llms_from_scratch.ch04 import (
    LayerNorm,
    GELU,
    FeedForward,
    TransformerBlock,
    GPTModel,
    GPTModelFast # Bonus: Faster variant using PyTorch's scaled_dot_product_attention
    generate_text_simple
)

from llms_from_scratch.ch05 import (
    generate,
    train_model_simple,
    evaluate_model,
    generate_and_print_sample,
    assign,
    load_weights_into_gpt,
    text_to_token_ids,
    token_ids_to_text,
    calc_loss_batch,
    calc_loss_loader,
    plot_losses,
    download_and_load_gpt2
)

from llms_from_scratch.ch06 import (
    download_and_unzip_spam_data,
    create_balanced_dataset,
    random_split,
    SpamDataset,
    calc_accuracy_loader,
    evaluate_model,
    train_classifier_simple,
    plot_values,
    classify_review
)

from llms_from_scratch.ch07 import (
    download_and_load_file,
    format_input,
    InstructionDataset,
    custom_collate_fn,
    check_if_running,
    query_model,
    generate_model_scores
)

	
from llms_from_scratch.appendix_a import NeuralNetwork, ToyDataset

from llms_from_scratch.appendix_d import find_highest_gradient, train_model