Skip to content

Update monarch_distributed_tutorial.rst #3786

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
sekyondaMeta wants to merge 2 commits into
base: main
Choose a base branch
from
+2 −2
Open

Update monarch_distributed_tutorial.rst #3786

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
a85553d
Update monarch_distributed_tutorial.rst
sekyondaMeta Mar 2, 2026
ee73287
Update monarch_distributed_tutorial.rst
sekyondaMeta Mar 2, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions intermediate_source/monarch_distributed_tutorial.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ We rely on a nightly build of Titan for this tutorial, so please ensure that oth
`Install script <https://github.com/meta-pytorch/monarch/blob/main/scripts/install_nightly.py>`_
2. **TorchTitan nightly installed:**
`TorchTitan install instructions <https://github.com/pytorch/torchtitan?tab=readme-ov-file#nightly-builds>`_
3. **A valid Titan model config** and **tokenizer** in your working directory (e.g., ``debug_model.toml`` from `TorchTitan configs <https://github.com/pytorch/torchtitan/blob/main/torchtitan/models/llama3/train_configs/debug_model.toml>`_).
3. **A valid Titan model config** and **tokenizer** in your working directory
4. **SLURM cluster access:**

- Sufficient permissions to reserve nodes and launch jobs.
Expand Down Expand Up @@ -446,4 +446,4 @@ TorchTitan for scalable distributed training.
**Further Reading**

- Monarch also integrates with TorchFT to provide per-step fault-tolerance across replicated workers. You can find a comprehensive `proof of concept <https://github.com/meta-pytorch/torchft/tree/main/examples/monarch>`_ of this integration in the TorchFT repo.
- For an interactive notebook covering similar topics to this tutorial, please consult `this Monarch example <https://github.com/meta-pytorch/monarch/blob/main/examples/slurm_titan.ipynb>`_.
- For an interactive notebook covering similar topics to this tutorial, please consult `this Monarch example <https://github.com/meta-pytorch/monarch/blob/main/examples/slurm_titan.ipynb>`_.