From 2cf1d0c56ec3631c35a712e2c618ccfdd6ec395e Mon Sep 17 00:00:00 2001 From: Deven Navani Date: Wed, 7 Aug 2024 15:58:08 +0000 Subject: [PATCH] Fix broken links to guide/custom-container --- 06_gpu_and_ml/llm-serving/trtllm_llama.py | 2 +- 06_gpu_and_ml/tensorflow/tensorflow_tutorial.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/06_gpu_and_ml/llm-serving/trtllm_llama.py b/06_gpu_and_ml/llm-serving/trtllm_llama.py index 1fb053484..b91a4f570 100644 --- a/06_gpu_and_ml/llm-serving/trtllm_llama.py +++ b/06_gpu_and_ml/llm-serving/trtllm_llama.py @@ -43,7 +43,7 @@ # # To run TensorRT-LLM, we must first install it. Easier said than done! # -# In Modal, we define [container images](https://modal.com/docs/guide/custom-containers) that run our serverless workloads. +# In Modal, we define [container images](https://modal.com/docs/guide/custom-container) that run our serverless workloads. # All Modal containers have access to GPU drivers via the underlying host environment, # but we still need to install the software stack on top of the drivers, from the CUDA runtime up. # diff --git a/06_gpu_and_ml/tensorflow/tensorflow_tutorial.py b/06_gpu_and_ml/tensorflow/tensorflow_tutorial.py index ba141c163..c0659b097 100644 --- a/06_gpu_and_ml/tensorflow/tensorflow_tutorial.py +++ b/06_gpu_and_ml/tensorflow/tensorflow_tutorial.py @@ -15,7 +15,7 @@ # # Configuring a system to properly run GPU-accelerated TensorFlow can be challenging. # Luckily, Modal makes it easy to stand on the shoulders of giants and -# [use a pre-built Docker container image](https://modal.com/docs/guide/custom-containers#use-an-existing-container-image-with-from_registry) from a registry like Docker Hub. +# [use a pre-built Docker container image](https://modal.com/docs/guide/custom-container#use-an-existing-container-image-with-from_registry) from a registry like Docker Hub. # We recommend TensorFlow's [official base Docker container images](https://hub.docker.com/r/tensorflow/tensorflow), which come with `tensorflow` and its matching CUDA libraries already installed. # # If you want to install TensorFlow some other way, check out [their docs](https://www.tensorflow.org/install) for options and instructions.