Apply suggestions from code review

.github/scripts/spellcheck_conf/wordlist.txt

@@ -1411,4 +1411,5 @@ tp
 QLoRA
 ntasks
 srun
-xH
+xH
+unquantized

recipes/3p_integrations/vllm/README.md

@@ -30,7 +30,7 @@ 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
-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.
+The FP8 quantized variants 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.

recipes/quickstart/inference/local_inference/README.md

@@ -86,5 +86,5 @@ python inference.py --model_name <training_config.output_dir> --prompt_file <tes
 ```
 
 ## Inference on large models like Meta Llama 405B
-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.
+The FP8 quantized variants 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).