diff --git a/docs/docs/install/environment-variables.md b/docs/docs/install/environment-variables.md
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--- a/docs/docs/install/environment-variables.md
+++ b/docs/docs/install/environment-variables.md
@@ -154,33 +154,33 @@ Redis (Sentinel) URL example JSON before encoding:
## Machine Learning
-| Variable | Description | Default | Containers |
-| :---------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------- | :-----------------------------: | :--------------- |
-| `MACHINE_LEARNING_MODEL_TTL` | Inactivity time (s) before a model is unloaded (disabled if \<= 0) | `300` | machine learning |
-| `MACHINE_LEARNING_MODEL_TTL_POLL_S` | Interval (s) between checks for the model TTL (disabled if \<= 0) | `10` | machine learning |
-| `MACHINE_LEARNING_CACHE_FOLDER` | Directory where models are downloaded | `/cache` | machine learning |
-| `MACHINE_LEARNING_REQUEST_THREADS`\*1 | Thread count of the request thread pool (disabled if \<= 0) | number of CPU cores | machine learning |
-| `MACHINE_LEARNING_MODEL_INTER_OP_THREADS` | Number of parallel model operations | `1` | machine learning |
-| `MACHINE_LEARNING_MODEL_INTRA_OP_THREADS` | Number of threads for each model operation | `2` | machine learning |
-| `MACHINE_LEARNING_WORKERS`\*2 | Number of worker processes to spawn | `1` | machine learning |
-| `MACHINE_LEARNING_HTTP_KEEPALIVE_TIMEOUT_S`\*3 | HTTP Keep-alive time in seconds | `2` | machine learning |
-| `MACHINE_LEARNING_WORKER_TIMEOUT` | Maximum time (s) of unresponsiveness before a worker is killed | `300` (`900` if using ROCm) | machine learning |
-| `MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL` | Comma-separated list of (textual) CLIP model(s) to preload and cache | | machine learning |
-| `MACHINE_LEARNING_PRELOAD__CLIP__VISUAL` | Comma-separated list of (visual) CLIP model(s) to preload and cache | | machine learning |
-| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION` | Comma-separated list of (recognition) facial recognition model(s) to preload and cache | | machine learning |
-| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION` | Comma-separated list of (detection) facial recognition model(s) to preload and cache | | machine learning |
-| `MACHINE_LEARNING_PRELOAD__OCR__RECOGNITION` | Comma-separated list of (recognition) OCR model(s) to preload and cache | | machine learning |
-| `MACHINE_LEARNING_PRELOAD__OCR__DETECTION` | Comma-separated list of (detection) OCR model(s) to preload and cache | | machine learning |
-| `MACHINE_LEARNING_ANN` | Enable ARM-NN hardware acceleration if supported | `True` | machine learning |
-| `MACHINE_LEARNING_ANN_FP16_TURBO` | Execute operations in FP16 precision: increasing speed, reducing precision (applies only to ARM-NN) | `False` | machine learning |
-| `MACHINE_LEARNING_ANN_TUNING_LEVEL` | ARM-NN GPU tuning level (1: rapid, 2: normal, 3: exhaustive) | `2` | machine learning |
-| `MACHINE_LEARNING_DEVICE_IDS`\*4 | Device IDs to use in multi-GPU environments | `0` | machine learning |
-| `MACHINE_LEARNING_MAX_BATCH_SIZE__FACIAL_RECOGNITION` | Set the maximum number of faces that will be processed at once by the facial recognition model | None (`1` if using OpenVINO) | machine learning |
-| `MACHINE_LEARNING_MAX_BATCH_SIZE__OCR` | Set the maximum number of boxes that will be processed at once by the OCR model | `6` | machine learning |
-| `MACHINE_LEARNING_RKNN` | Enable RKNN hardware acceleration if supported | `True` | machine learning |
-| `MACHINE_LEARNING_RKNN_THREADS` | How many threads of RKNN runtime should be spun up while inferencing. | `1` | machine learning |
-| `MACHINE_LEARNING_MODEL_ARENA` | Pre-allocates CPU memory to avoid memory fragmentation | true | machine learning |
-| `MACHINE_LEARNING_OPENVINO_PRECISION` | If set to FP16, uses half-precision floating-point operations for faster inference with reduced accuracy (one of [`FP16`, `FP32`], applies only to OpenVINO) | `FP32` | machine learning |
+| Variable | Description | Default | Containers |
+| :---------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------------------------: | :--------------- |
+| `MACHINE_LEARNING_MODEL_TTL` | Inactivity time (s) before a model is unloaded (disabled if \<= 0) | `300` | machine learning |
+| `MACHINE_LEARNING_MODEL_TTL_POLL_S` | Interval (s) between checks for the model TTL (disabled if \<= 0) | `10` | machine learning |
+| `MACHINE_LEARNING_CACHE_FOLDER` | Directory where models are downloaded | `/cache` | machine learning |
+| `MACHINE_LEARNING_REQUEST_THREADS`\*1 | Thread count of the request thread pool (disabled if \<= 0) | number of CPU cores | machine learning |
+| `MACHINE_LEARNING_MODEL_INTER_OP_THREADS` | Number of parallel model operations | `1` | machine learning |
+| `MACHINE_LEARNING_MODEL_INTRA_OP_THREADS` | Number of threads for each model operation | `2` | machine learning |
+| `MACHINE_LEARNING_WORKERS`\*2 | Number of worker processes to spawn | `1` | machine learning |
+| `MACHINE_LEARNING_HTTP_KEEPALIVE_TIMEOUT_S`\*3 | HTTP Keep-alive time in seconds | `2` | machine learning |
+| `MACHINE_LEARNING_WORKER_TIMEOUT` | Maximum time (s) of unresponsiveness before a worker is killed | `300` (`900` if using ROCm) | machine learning |
+| `MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL` | Comma-separated list of (textual) CLIP model(s) to preload and cache | | machine learning |
+| `MACHINE_LEARNING_PRELOAD__CLIP__VISUAL` | Comma-separated list of (visual) CLIP model(s) to preload and cache | | machine learning |
+| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION` | Comma-separated list of (recognition) facial recognition model(s) to preload and cache | | machine learning |
+| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION` | Comma-separated list of (detection) facial recognition model(s) to preload and cache | | machine learning |
+| `MACHINE_LEARNING_PRELOAD__OCR__RECOGNITION` | Comma-separated list of (recognition) OCR model(s) to preload and cache | | machine learning |
+| `MACHINE_LEARNING_PRELOAD__OCR__DETECTION` | Comma-separated list of (detection) OCR model(s) to preload and cache | | machine learning |
+| `MACHINE_LEARNING_ANN` | Enable ARM-NN hardware acceleration if supported | `True` | machine learning |
+| `MACHINE_LEARNING_ANN_FP16_TURBO` | Execute operations in FP16 precision: increasing speed, reducing precision (applies only to ARM-NN) | `False` | machine learning |
+| `MACHINE_LEARNING_ANN_TUNING_LEVEL` | ARM-NN GPU tuning level (1: rapid, 2: normal, 3: exhaustive) | `2` | machine learning |
+| `MACHINE_LEARNING_DEVICE_IDS`\*4 | Device IDs to use in multi-GPU environments | `0` | machine learning |
+| `MACHINE_LEARNING_MAX_BATCH_SIZE__FACIAL_RECOGNITION` | Set the maximum number of faces that will be processed at once by the facial recognition model | None (`1` if using OpenVINO) | machine learning |
+| `MACHINE_LEARNING_MAX_BATCH_SIZE__OCR` | Set the maximum number of boxes that will be processed at once by the OCR model | `6` | machine learning |
+| `MACHINE_LEARNING_RKNN` | Enable RKNN hardware acceleration if supported | `True` | machine learning |
+| `MACHINE_LEARNING_RKNN_THREADS` | How many threads of RKNN runtime should be spun up while inferencing. | `1` | machine learning |
+| `MACHINE_LEARNING_MODEL_ARENA` | Pre-allocates CPU memory to avoid memory fragmentation | true | machine learning |
+| `MACHINE_LEARNING_OPENVINO_PRECISION` | If set to FP16, uses half-precision floating-point operations for faster inference with reduced accuracy (one of [`FP16`, `FP32`], applies only to OpenVINO) | `FP32` | machine learning |
\*1: It is recommended to begin with this parameter when changing the concurrency levels of the machine learning service and then tune the other ones.