charlesfrye

# Train GPT-2 in five minutes -- for free
#
# ```bash
# pip install modal
# modal setup
# modal run wrapper.py
# ```
#
# Note that the end-to-end latency the first time is more like 25 minutes:
# - five minutes to install Torch (rip)

charlesfrye

See rune2e.sh for info on how to run the experiment.

charlesfrye

import modal

vllm_image = modal.Image.debian_slim(python_version="3.10").pip_install(
    [
        "vllm==0.5.3post1",  # LLM serving
        "huggingface_hub==0.24.1",  # download models from the Hugging Face Hub
        "hf-transfer==0.1.8",  # download models faster
    ]
)

charlesfrye

import os
import subprocess

import modal

MODEL_NAME = "meta-llama/Meta-Llama-3-8B-Instruct"
MODEL_DIR = f"/models/{MODEL_NAME}"

N_GPU = 1

charlesfrye

log --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit

To configure as an alias git lol:

git config --global alias.lol "log --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit"

charlesfrye

import ipywidgets

ipywidgets.IntSlider()

charlesfrye

import flake8
from flake8.formatting import base as formatter
from flake8.main import application as app
import flake8.options.config as config

application = app.Application()

application.parse_preliminary_options_and_args([])
flake8.configure_logging(
        application.prelim_opts.verbose, application.prelim_opts.output_file