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Update spawn_actors API in sft v2 main.py #307

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Merged
merged 2 commits into from
Oct 3, 2025
Merged

Update spawn_actors API in sft v2 main.py #307

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1a21945
fix sft v2
daniellepintz Oct 3, 2025
e4a7d48
upd
daniellepintz Oct 3, 2025
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10 changes: 6 additions & 4 deletions apps/sft_v2/llama3_8b.yaml
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Original file line number Diff line number Diff line change
@@ -1,9 +1,11 @@
# >>> python -m apps.sft_v2.main --config apps/sft_v2/llama3_8b.yaml

# Config for supervised full finetuning using a Llama3.1 8B Instruct model
#
# This config assumes that you've run the following command before launching
# this run:
# export HF_HUB_DISABLE_XET=1
# uv run forge download meta-llama/Meta-Llama-3.1-8B-Instruct
# forge download meta-llama/Meta-Llama-3.1-8B-Instruct --output-dir /tmp/Meta-Llama-3.1-8B-Instruct
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I didn't have uv installed so this cmd didn't work. is uv necessary?

also, do we still need to do export HF_HUB_DISABLE_XET=1?

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i tried 'HF_HUB_DISABLE_XET=1 about ~1 week ago and it broke. I dont think it works well with our devmachines. @joecummings do you know?



# TODO: required by torchtitan
Expand All @@ -14,11 +16,11 @@ comm:
model:
name: llama3
flavor: 8B
tokenizer_path: /tmp/Llama-3.1-8B-Instruct
hf_assets_path: /tmp/Meta-Llama-3.1-8B-Instruct

processes:
scheduler: local # local | mast (not supported yet)
hosts: 1
# scheduler: local # local | mast (not supported yet)
# hosts: 1
procs: 8
with_gpus: true

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18 changes: 6 additions & 12 deletions apps/sft_v2/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@

import torchtitan.experiments.forge.train_spec as forge_train_spec
from forge.cli.config import parse
from forge.controller import ForgeActor, spawn_actors
from forge.controller import ForgeActor
from forge.data.collate import collate_packed
from forge.data.datasets.packed import PackedDataset, TextPacker
from forge.data.datasets.sft_dataset import AlpacaToMessages, sft_iterable_dataset
Expand Down Expand Up @@ -130,16 +130,16 @@ async def setup(self):
# self.logger = self.setup_logger(self.train_config.logger_config)

def setup_data(self):
print(os.path.join(self.job_config.model.tokenizer_path, "tokenizer.json"))
print(os.path.join(self.job_config.model.hf_assets_path, "tokenizer.json"))
tokenizer = HuggingFaceModelTokenizer(
tokenizer_json_path=os.path.join(
self.job_config.model.tokenizer_path, "tokenizer.json"
self.job_config.model.hf_assets_path, "tokenizer.json"
),
tokenizer_config_json_path=os.path.join(
self.job_config.model.tokenizer_path, "tokenizer_config.json"
self.job_config.model.hf_assets_path, "tokenizer_config.json"
),
generation_config_path=os.path.join(
self.job_config.model.tokenizer_path, "generation_config.json"
self.job_config.model.hf_assets_path, "generation_config.json"
),
)

Expand Down Expand Up @@ -280,13 +280,7 @@ def __repr__(self) -> str:
async def run(cfg: DictConfig) -> None:
logging.info("Spawing recipe...")
process_cfg = cfg.pop("processes")
recipe = await spawn_actors(
"sft",
ForgeSFTRecipe,
{"config": cfg},
process_cfg,
set_address=True,
)
recipe = await ForgeSFTRecipe.options(**process_cfg).as_service(cfg)

logging.info("Created recipe, running setup.")
await recipe.setup.fanout()
Expand Down
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