From b9198d076b43a3769494fb0ee2682096fdf37ded Mon Sep 17 00:00:00 2001
From: markus583 <markus.frohmann@gmail.com>
Date: Sun, 22 Sep 2024 15:22:08 +0200
Subject: [PATCH] remove exact timings.

---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index a0f04d69..914c56a5 100644
--- a/README.md
+++ b/README.md
@@ -60,13 +60,13 @@ sat = SaT("sat-3l-sm", onnx_providers=["CUDAExecutionProvider"])
 # PyTorch GPU
 >>> model = SaT("sat-3l-sm")
 >>> model.half().to("cuda")
->>> %timeit list(model.split(texts))
-138 ms ± 8.41 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
+>>> list(model.split(texts))
+# quite fast already, but...
 
 # onnxruntime GPU
 >>> model = SaT("sat-3l-sm", ort_providers=["CUDAExecutionProvider"])
 >>> %timeit list(model.split(texts))
-198 ms ± 1.36 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
+# ...this should be ~50% faster!
 ```
 
 If you wish to use LoRA in combination with an ONNX model: