[simonw]

I got your model working on CPU on macOS by having Claude Code hack away furiously for a while. Here's a script that should work for anyone: https://gist.github.com/simonw/912623bf00d6c13cc0211508969a1...

You can run it like this:

  cd /tmp
  git clone https://huggingface.co/sdobson/nanochat
  uv run https://gist.githubusercontent.com/simonw/912623bf00d6c13cc0211508969a100a/raw/80f79c6a6f1e1b5d4485368ef3ddafa5ce853131/generate_cpu.py \
    --model-dir /tmp/nanochat \
    --prompt "Tell me about dogs."

[sammyd56]

This is a much easier way to run the model. I'm going to update the huggingface README to point to this. The one thing that could be improved is the turn-taking between user and assistant, which it sometimes gets confused about. I fixed that in my fork of your gist here: https://gist.github.com/samdobson/975c8b095a71bbdf1488987eac...

[vessenes]

Simon, I had to run "brew install git-lfs && cd nano-chat && git lfs install && git lfs pull" and then it worked. before then, the model weights didn't get cloned by default for me on macOS.

% uv run https://gist.githubusercontent.com/simonw/912623bf00d6c13cc0... \ --model-dir nanochat/ --prompt "who is simonw on hacker news?" Using device: cpu Loading model from nanochat/model_000650.pt Loading metadata from nanochat/meta_000650.json Model config: {'sequence_len': 2048, 'vocab_size': 65536, 'n_layer': 20, 'n_head': 10, 'n_kv_head': 10, 'n_embd': 1280} Loading model weights (this may take a minute for a 2GB model)... Converting model to float32 for CPU... Model loaded successfully! Loading tokenizer... Tokenizer loaded successfully!

Prompt: who is simonw on hacker news? Encoded to 9 tokens

Generating... -------------------------------------------------- who is simonw on hacker news?<|user_end|><|assistant_start|>A hacker news reporter, I'd say a few things. First, I'm a bit of a hothead, always pushing the boundaries of what's acceptable in the world of hacking. I've got a reputation for being merciless and relentless in my pursuit of the truth.

In many ways, I've developed a sixth sense for this type of thing. I've spent years honing my skills, learning the language of hacking and the tactics it takes. I know how to think like the hacker --------------------------------------------------

[homeless_engi]

Adding on: Claude also gave me the following line which was necessary to get the model weights to download from HF. This might be obvious for anyone familiar with HF but it helped me so sharing here!

git lfs install

[iamcreasy]

For anyone curious this is the error when running uv sync on macos,

> uv sync Resolved 88 packages in 3ms error: Distribution `torch==2.8.0+cu128 @ registry+https://download.pytorch.org/whl/cu128` can't be installed because it doesn't have a source distribution or wheel for the current platform

hint: You're on macOS (`macosx_15_0_arm64`), but `torch` (v2.8.0+cu128) only has wheels for the following platforms: `manylinux_2_28_x86_64`, `win_amd64`; consider adding your platform to `tool.uv.required-environments` to ensure uv resolves to a version with compatible wheels

Also, tmp/nanochat expects all contents from tokenizer and chatsft_checkpoints folder.

[stoobs]

Yeah, that's because cuda on a mac isn't a thing - it could be swapped to the normal torch package but you'd have to do some code patching to make sure it's running on mps, even then some of the code may need rewriting/patching if there's no mps version of the cuda kernals.

[iamcreasy]

Isn't there a common PyTorch API interface that could chose OS/hardware specific backend automatically? Or this project is hard coding cuda variant of PyTorch as a requirement?