Skip to content

remove tips for attn_temperature_tuning in llama4 blog #51

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

Merged
merged 1 commit into from
Apr 15, 2025
Merged

remove tips for attn_temperature_tuning in llama4 blog #51

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
1 change: 0 additions & 1 deletion _posts/2025-04-05-llama4.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,6 @@ While more performance enhancements are on the way, we believe the Llama 4 model

* **Boost Performance & Context Length:** Set `--kv-cache-dtype fp8` to potentially double the usable context window and gain a performance boost. We observe little to no accuracy drop in relevant evaluations with this setting.
* **Maximize Context Window (up to 10M):** To fully utilize the maximum context windows (up to 10M for Scout), we recommend serving across multiple nodes using tensor parallelism or pipeline parallelism. Follow our distributed inference guide [here](https://docs.vllm.ai/en/latest/serving/distributed_serving.html).
* **Improve Long Context Accuracy (\>32K):** We highly recommend adding `--override-generation-config='{"attn_temperature_tuning": true}'` to improve accuracy for contexts longer than 32K tokens.

**Other Hardware Support & Quantizations:**

Expand Down
Loading