From 190d543b53f2c2bbfa54aad4ce26c4e9a2032f1a Mon Sep 17 00:00:00 2001
From: Matthias Reso <13337103+mreso@users.noreply.github.com>
Date: Mon, 22 Jul 2024 12:26:47 -0700
Subject: [PATCH] Add fp8 references

---
 recipes/3p_integrations/vllm/README.md                 | 3 ++-
 recipes/quickstart/inference/local_inference/README.md | 3 ++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/recipes/3p_integrations/vllm/README.md b/recipes/3p_integrations/vllm/README.md
index 17d79785..396c7288 100644
--- a/recipes/3p_integrations/vllm/README.md
+++ b/recipes/3p_integrations/vllm/README.md
@@ -30,7 +30,8 @@ The script will ask for another prompt ina loop after completing the generation
 When using multiple gpus the model will automatically be split accross the available GPUs using tensor parallelism.
 
 ## Multi-node multi-gpu inference
-Models like the unquantized variant of Meta-Llama-3.1-405B are too large to be executed on an single node and therefore need multi-node inference.
+The FP8 quantized veriants of Meta Llama (i.e. meta-llama/Meta-Llama-3.1-405B-FP8 and meta-llama/Meta-Llama-3.1-405B-Instruct-FP8) can be executed on a single node with 8x80GB H100 using the script located in this folder.
+To run the unquantized Meta Llama 405B variants (i.e. meta-llama/Meta-Llama-3.1-405B and meta-llama/Meta-Llama-3.1-405B-Instruct) we need multi-node inference.
 vLLM allows this by leveraging pipeline parallelism accros nodes while still applying tensor parallelism insid each node.
 To start a multi-node inference we first need to set up a ray serves which well be leveraged by vLLM to execute the model across node boundaries.
 
diff --git a/recipes/quickstart/inference/local_inference/README.md b/recipes/quickstart/inference/local_inference/README.md
index 2918d85e..a8afa076 100644
--- a/recipes/quickstart/inference/local_inference/README.md
+++ b/recipes/quickstart/inference/local_inference/README.md
@@ -86,4 +86,5 @@ python inference.py --model_name <training_config.output_dir> --prompt_file <tes
 ```
 
 ## Inference on large models like Meta Llama 405B
-To run the Meta Llama 405B variant without quantization we need to use a multi-node setup for inference. The llama-recipes inference script currently does not allow multi-node inference. To run this model you can use vLLM with pipeline and tensor parallelism as showed in [this example](../../../3p_integrations/vllm/README.md).
\ No newline at end of file
+The FP8 quantized veriants of Meta Llama (i.e. meta-llama/Meta-Llama-3.1-405B-FP8 and meta-llama/Meta-Llama-3.1-405B-Instruct-FP8) can be executed on a single node with 8x80GB H100 using the scripts located in this folder.
+To run the unquantized Meta Llama 405B variants (i.e. meta-llama/Meta-Llama-3.1-405B and meta-llama/Meta-Llama-3.1-405B-Instruct) we need to use a multi-node setup for inference. The llama-recipes inference script currently does not allow multi-node inference. To run this model you can use vLLM with pipeline and tensor parallelism as showed in [this example](../../../3p_integrations/vllm/README.md).
\ No newline at end of file
-- 
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