Skip to content

Add high-throughput batch processing cookbook for Nemotron 3 Super #109

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
mvanhorn wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Add high-throughput batch processing cookbook for Nemotron 3 Super #109

Show file tree
Hide file tree
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: 1 addition & 0 deletions usage-cookbook/Nemotron-3-Super/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ These notebooks provide end-to-end recipes for deploying and customizing Nemotro
- **[vllm_cookbook.ipynb](vllm_cookbook.ipynb)** — Deploy Nemotron-3-Super with vLLM.
- **[sglang_cookbook.ipynb](sglang_cookbook.ipynb)** — Deploy Nemotron-3-Super with SGLang.
- **[trtllm_cookbook.ipynb](trtllm_cookbook.ipynb)** — Deploy Nemotron-3-Super with TensorRT-LLM.
- **[batch_throughput_cookbook.ipynb](batch_throughput_cookbook.ipynb)** — High-throughput batch processing with vLLM: offline batch inference, concurrent server requests, bulk document classification, and throughput benchmarking.
- **{doc}`AdvancedDeploymentGuide <AdvancedDeploymentGuide/README>`** — Production deployment configurations for vLLM, SGLang, and TRT-LLM across GPU topologies (GB200, B200, DGX Spark), including MTP speculative decoding, expert parallelism, and tuning guidance.

### Fine-Tuning
Expand Down
Loading