FAQ file for TorchRec #3222
Open
FAQ file for TorchRec #3222
+112
−0
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
facebook-github-bot
added
the
CLA Signed
|
This pull request was exported from Phabricator. Differential Revision: D78769752 |
yupadhyay
force-pushed
the
export-D78769752
branch
from
01d66e9 to
f1e7737
Compare
yupadhyay
added a commit
to yupadhyay/torchrec
that referenced
this pull request
Jul 31, 2025
Summary: docs: Add FAQ for TorchRec This commit introduces a new FAQ.md file to address common questions regarding TorchRec for large model and embedding training. The FAQ covers: - General concepts and use cases for TorchRec and FSDP. - Sharding strategies and distributed training in TorchRec. - Memory management and performance optimization for large embedding tables. - Integration with existing systems. - Common technical challenges encountered by users. - Best practices for model design and evaluation. The goal is to provide a comprehensive resource for users facing challenges with large-scale recommendation systems and distributed training, improving clarity and reducing common pain points. Differential Revision: D78769752
yupadhyay
added a commit
to yupadhyay/torchrec
that referenced
this pull request
Jul 31, 2025
Summary: docs: Add FAQ for TorchRec This commit introduces a new FAQ.md file to address common questions regarding TorchRec for large model and embedding training. The FAQ covers: - General concepts and use cases for TorchRec and FSDP. - Sharding strategies and distributed training in TorchRec. - Memory management and performance optimization for large embedding tables. - Integration with existing systems. - Common technical challenges encountered by users. - Best practices for model design and evaluation. The goal is to provide a comprehensive resource for users facing challenges with large-scale recommendation systems and distributed training, improving clarity and reducing common pain points. Differential Revision: D78769752
yupadhyay
force-pushed
the
export-D78769752
branch
from
f1e7737 to
b8d5210
Compare
|
This pull request was exported from Phabricator. Differential Revision: D78769752 |
yupadhyay
added a commit
to yupadhyay/torchrec
that referenced
this pull request
Jul 31, 2025
Summary: Pull Request resolved: pytorch#3222 docs: Add FAQ for TorchRec This commit introduces a new FAQ.md file to address common questions regarding TorchRec for large model and embedding training. The FAQ covers: - General concepts and use cases for TorchRec and FSDP. - Sharding strategies and distributed training in TorchRec. - Memory management and performance optimization for large embedding tables. - Integration with existing systems. - Common technical challenges encountered by users. - Best practices for model design and evaluation. The goal is to provide a comprehensive resource for users facing challenges with large-scale recommendation systems and distributed training, improving clarity and reducing common pain points. Differential Revision: D78769752
|
This pull request was exported from Phabricator. Differential Revision: D78769752 |
yupadhyay
force-pushed
the
export-D78769752
branch
from
b8d5210 to
c467caa
Compare
|
This pull request was exported from Phabricator. Differential Revision: D78769752 |
Summary: Pull Request resolved: pytorch#3222 docs: Add FAQ for TorchRec This commit introduces a new FAQ.md file to address common questions regarding TorchRec for large model and embedding training. The FAQ covers: - General concepts and use cases for TorchRec and FSDP. - Sharding strategies and distributed training in TorchRec. - Memory management and performance optimization for large embedding tables. - Integration with existing systems. - Common technical challenges encountered by users. - Best practices for model design and evaluation. The goal is to provide a comprehensive resource for users facing challenges with large-scale recommendation systems and distributed training, improving clarity and reducing common pain points. Differential Revision: D78769752
yupadhyay
force-pushed
the
export-D78769752
branch
from
c467caa to
640fc67
Compare
|
This pull request was exported from Phabricator. Differential Revision: D78769752 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary:
docs: Add FAQ for TorchRec
This commit introduces a new FAQ.md file to address common questions regarding TorchRec for large model and embedding training.
The FAQ covers:
The goal is to provide a comprehensive resource for users facing challenges with large-scale recommendation systems and distributed training, improving clarity and reducing common pain points.
Differential Revision: D78769752