diff --git a/src/sparseml/transformers/sparsification/obcq/README.md b/src/sparseml/transformers/sparsification/obcq/README.md
index 88092a173a6..68c356b066d 100644
--- a/src/sparseml/transformers/sparsification/obcq/README.md
+++ b/src/sparseml/transformers/sparsification/obcq/README.md
@@ -3,13 +3,7 @@ This page describes how to perform one-shot quantization of large language model
 
 ### Note on system requirements
 
-Due to inefficiencies in PyTorch ONNX export, a lot of system memory is required to export the models for inference. Below are some current estimations for various model sizes using `torch==2.1`. There are [improvements coming in 2.2](https://github.com/pytorch/pytorch/commit/b4a49124c8165a374a3ef49e14807ac05b3fc030).
-
-| Model Size  | Required GPU VRAM | Required System RAM |
-| ----------- | ----------- | ----------- |
-| 1B Params   | 16GB        | 64GB |
-| 7B Params   | 32GB        | ~300GB |
-| 13B Params  | 64GB        | ~600GB |
+Due to inefficiencies in PyTorch ONNX export, a lot of system memory is required to export the models for inference. There are [improvements coming in 2.2](https://github.com/pytorch/pytorch/commit/b4a49124c8165a374a3ef49e14807ac05b3fc030).
 
 ## Table of Contents 
 1. [How to Clone and Install  the Latest SparseML](#clone)