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GATEOverflow · Jun 18, 2024 · 7b67559 · 7b67559
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diff --git a/docs/benchmarks/image_classification/mobilenets.md b/docs/benchmarks/image_classification/mobilenets.md
@@ -7,53 +7,63 @@ Mobilenet models are not official MLPerf models and so cannot be used for a Clos
 === "Mobilenet-V1"
     ### Mobilenet V1
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_mobilenet-v1 --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_mobilenet-v1 \
+     --adr.compiler.tags=gcc
     ```
 === "Mobilenet-V2"
     ### Mobilenet V2
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_mobilenet-v2 --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_mobilenet-v2 \
+     --adr.compiler.tags=gcc
     ```
 === "Mobilenet-V2"
     ### Mobilenet V2
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_mobilenet-v2 --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_mobilenet-v2 \
+     --adr.compiler.tags=gcc
     ```
 === "Mobilenets"
     ### Mobilenet V1,V2,V3
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_mobilenet --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_mobilenet \
+     --adr.compiler.tags=gcc
     ```
 === "Efficientnet"
     ### Efficientnet
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_efficientnet --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_efficientnet \
+     --adr.compiler.tags=gcc
     ```
 
 ## ARMNN Backend
 === "Mobilenet-V1"
     ### Mobilenet V1
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet-v1 --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet-v1 \
+     --adr.compiler.tags=gcc
     ```
 === "Mobilenet-V2"
     ### Mobilenet V2
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet-v2 --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet-v2 \
+     --adr.compiler.tags=gcc
     ```
 === "Mobilenet-V2"
     ### Mobilenet V2
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet-v2 --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet-v2 \
+     --adr.compiler.tags=gcc
     ```
 === "Mobilenets"
     ### Mobilenet V1,V2,V3
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_armnn,_mobilenet \
+     --adr.compiler.tags=gcc
     ```
 === "Efficientnet"
     ### Efficientnet
     ```bash
-       cm run script --tags=run,mobilenet-models,_tflite,_armnn,_efficientnet --adr.compiler.tags=gcc
+    cm run script --tags=run,mobilenet-models,_tflite,_armnn,_efficientnet \
+     --adr.compiler.tags=gcc
     ```
 
diff --git a/docs/install/index.md b/docs/install/index.md
@@ -1,12 +1,18 @@
 # Installation
 We use MLCommons CM Automation framework to run MLPerf inference benchmarks.
 
-Please follow the [official installation page](https://docs.mlcommons.org/ck/install) to install CM
+CM needs `git`, `python3-pip` and `python3-venv` installed on your system. If any of these are absent, please follow the [official CM installation page](https://docs.mlcommons.org/ck/install) to install them. Once the dependencies are installed, do the following
 
-## Download the CM MLOps Repository
+## Activate a VENV for CM
+```bash
+   python3 -m venv cm
+   source cm/bin/activate
+```
+
+## Install CM and pulls any needed repositories
 
 ```bash
-   cm pull repo gateoverflow@cm4mlops
+   pip install cm4mlops
 ```
 
 

diff --git a/language/mixtral-8x7b/README.md b/language/mixtral-8x7b/README.md
@@ -95,6 +95,20 @@ Alternatively, you can simply cd into the folder where you want to place the dat
 wget https://inference.mlcommons-storage.org/mixtral_8x7b%2F2024.06.06_mixtral_15k_v4.pkl
 ```
 
+### Calibration dataset
+
+#### Using Rclone
+Rclone is installed, cd into the folder where you want to place the dataset and run:
+```bash
+rclone copyurl https://inference.mlcommons-storage.org/mixtral_8x7b%2F2024.06.06_mixtral_15k_calibration_v4.pkl ./ -a -P
+```
+
+#### Using wget
+
+Alternatively, you can simply cd into the folder where you want to place the dataset and run
+```bash
+wget https://inference.mlcommons-storage.org/mixtral_8x7b%2F2024.06.06_mixtral_15k_calibration_v4.pkl
+```
 ### Unprocessed
 
 TODO: Share instructions and scripts