-
Notifications
You must be signed in to change notification settings - Fork 357
support eval of float8_a1x128_w128x128 #3269
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.
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
vkuzo
wants to merge
4
commits into
gh/vkuzo/160/head
Choose a base branch
from
gh/vkuzo/161/head
base: gh/vkuzo/160/head
Could not load branches
Branch not found: {{ refName }}
Loading
Could not load tags
Nothing to show
Loading
Are you sure you want to change the base?
Some commits from the old base branch may be removed from the timeline,
and old review comments may become outdated.
Open
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
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3269
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ✅ No FailuresAs of commit cafe668 with merge base f856d36 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
vkuzo
added a commit
that referenced
this pull request
Oct 31, 2025
Summary:
Adds support for the new float8 scaling recipe in the official eval
scripts used to generate accuracy numbers in the README.
For now, I am using this as a smoke test that the scaling is working on
a real model - it is. We can add official benchmark results after we
hook up slayton's cuBLAS binding on H100, which should make the UEX of
running evals a lot better.
Test Plan:
Smoke test on LLama-3.1-8B, accuracy looks good
```
// download checkpoint
with-proxy python scripts/download.py --hf_token {token} --repo_id meta-llama/Meta-Llama-3.1-8B
// prepare checkpoint
python scripts/convert_hf_checkpoint.py --checkpoint_dir checkpoints/meta-llama/Meta-Llama-3.1-8B
// run bf16 eval on a single task
with-proxy time python torchao/_models/llama/eval.py --checkpoint_path checkpoints/meta-llama/Meta-Llama-3.1-8B/model.pth --tasks 'winogrande'
...
winogrande: {'alias': 'winogrande', 'acc,none': 0.7426992896606156, 'acc_stderr,none': 0.012285989618865697}
// run float8 eval on the same task
with-proxy time python torchao/_models/llama/eval.py --checkpoint_path checkpoints/meta-llama/Meta-Llama-3.1-8B/model.pth --tasks 'winogrande' --quantization float8_a1x128_w128x128 --compile
...
winogrande: {'alias': 'winogrande', 'acc,none': 0.7419100236779794, 'acc_stderr,none': 0.012298278833972477}
```
Reviewers:
Subscribers:
Tasks:
Tags:
ghstack-source-id: 01b8d77
ghstack-comment-id: 3474380821
Pull-Request: #3269
This was referenced Oct 31, 2025
vkuzo
added a commit
that referenced
this pull request
Oct 31, 2025
Summary:
Adds support for the new float8 scaling recipe in the official eval
scripts used to generate accuracy numbers in the README.
For now, I am using this as a smoke test that the scaling is working on
a real model - it is. We can add official benchmark results after we
hook up slayton's cuBLAS binding on H100, which should make the UEX of
running evals a lot better.
Test Plan:
Smoke test on LLama-3.1-8B, accuracy looks good
```
// download checkpoint
with-proxy python scripts/download.py --hf_token {token} --repo_id meta-llama/Meta-Llama-3.1-8B
// prepare checkpoint
python scripts/convert_hf_checkpoint.py --checkpoint_dir checkpoints/meta-llama/Meta-Llama-3.1-8B
// run bf16 eval on a single task
with-proxy time python torchao/_models/llama/eval.py --checkpoint_path checkpoints/meta-llama/Meta-Llama-3.1-8B/model.pth --tasks 'winogrande'
...
winogrande: {'alias': 'winogrande', 'acc,none': 0.7426992896606156, 'acc_stderr,none': 0.012285989618865697}
// run float8 eval on the same task
with-proxy time python torchao/_models/llama/eval.py --checkpoint_path checkpoints/meta-llama/Meta-Llama-3.1-8B/model.pth --tasks 'winogrande' --quantization float8_a1x128_w128x128 --compile
...
winogrande: {'alias': 'winogrande', 'acc,none': 0.7419100236779794, 'acc_stderr,none': 0.012298278833972477}
```
Reviewers:
Subscribers:
Tasks:
Tags:
ghstack-source-id: e87609a
ghstack-comment-id: 3474380821
Pull-Request: #3269
vkuzo
added a commit
that referenced
this pull request
Oct 31, 2025
Summary:
Adds support for the new float8 scaling recipe in the official eval
scripts used to generate accuracy numbers in the README.
For now, I am using this as a smoke test that the scaling is working on
a real model - it is. We can add official benchmark results after we
hook up slayton's cuBLAS binding on H100, which should make the UEX of
running evals a lot better.
Test Plan:
Smoke test on LLama-3.1-8B, accuracy looks good
```
// download checkpoint
with-proxy python scripts/download.py --hf_token {token} --repo_id meta-llama/Meta-Llama-3.1-8B
// prepare checkpoint
python scripts/convert_hf_checkpoint.py --checkpoint_dir checkpoints/meta-llama/Meta-Llama-3.1-8B
// run bf16 eval on a single task
with-proxy time python torchao/_models/llama/eval.py --checkpoint_path checkpoints/meta-llama/Meta-Llama-3.1-8B/model.pth --tasks 'winogrande'
...
winogrande: {'alias': 'winogrande', 'acc,none': 0.7426992896606156, 'acc_stderr,none': 0.012285989618865697}
// run float8 eval on the same task
with-proxy time python torchao/_models/llama/eval.py --checkpoint_path checkpoints/meta-llama/Meta-Llama-3.1-8B/model.pth --tasks 'winogrande' --quantization float8_a1x128_w128x128 --compile
...
winogrande: {'alias': 'winogrande', 'acc,none': 0.7419100236779794, 'acc_stderr,none': 0.012298278833972477}
```
Reviewers:
Subscribers:
Tasks:
Tags:
ghstack-source-id: e87609a
ghstack-comment-id: 3474380821
Pull-Request: #3269
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Labels
CLA Signed
This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.
topic: for developers
Use this tag if this PR is mainly developer facing
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:
Adds support for the new float8 scaling recipe in the official eval
scripts used to generate accuracy numbers in the README.
For now, I am using this as a smoke test that the scaling is working on
a real model - it is. We can add official benchmark results after we
hook up the cuBLAS binding on H100, which should make the UEX of
running evals a lot better.
Test Plan:
Smoke test on LLama-3.1-8B, accuracy looks good
Reviewers:
Subscribers:
Tasks:
Tags: