Download total text container

Is in place, the next step is to add styling to the invoice generator using CSS. CSS allows us to control the visual appearance of the website, including things like layout, color, and typography.Next, we will create our CSS file. In this file, we will use some basic CSS rules to create our invoice generator.Here's an explanation of each section:The first block * sets the margin and padding of all elements on the page to 0, effectively removing any default spacing.The body selector styles the body element. It sets the font family to "roboto" and the background color to white.The .material-icons class is used to style elements with the "material-icons" class. It sets the cursor to a pointer, indicating interactivity.The .invoice-container class is applied to a container element for an invoice. It centers the container horizontally (margin: auto) and adds padding to the top and bottom (padding: 0px 20px).The .invoice-header class is applied to the header section of the invoice. It uses flexbox to display its contents in a row (display: flex), adds padding to the top and bottom (padding: 70px 0%), and sets the width to 100%.The .title, .date, and .invoice-number classes style various elements within the header section. They set font sizes, letter spacing, and colors for text.The .space class is applied to a container that occupies 50% of the width.The table selector styles table elements. It sets the table layout to "auto" and the width to 100%.The th and td selectors style table headers and table cells, respectively. They set padding, borders, font sizes, letter spacing, and colors for text.The .dashed class adds a dashed border-bottom style to elements.The .total class styles elements represent the total amount. It sets the font weight, font size, and color.The input[type=number] and input[type=text] selectors style input elements of type "number" and "text," respectively. They set text alignment, max width, font size, padding, border, and outline properties.The input[type=text]:focus and input[type=number]:focus selectors style the focused state of the input elements. They add a border radius and box shadow to create a visual effect.The input::-webkit-outer-spin-button and input::-webkit-inner-spin-button selectors style the appearance of spin buttons for number inputs in webkit-based browsers.The input[type=number] selector overrides the appearance of number inputs in Firefox.The .float class styles a floating circular element. It sets the width, height, background color, text color, border radius, text alignment, and box shadow.The .float:hover class styles the floating circular element when hovered. It changes

Skip to main content This browser is no longer supported. Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support. Custom speech to text containers with Docker Article03/10/2025 In this article -->The custom speech to text container transcribes real-time speech or batch audio recordings with intermediate results. You can use a custom model that you created in the custom speech portal. In this article, you learn how to download, install, and run a custom speech to text container.For more information about prerequisites, validating that a container is running, running multiple containers on the same host, and running disconnected containers, see Install and run Speech containers with Docker.Container imagesThe custom speech to text container image for all supported versions and locales can be found on the Microsoft Container Registry (MCR) syndicate. It resides within the azure-cognitive-services/speechservices/ repository and is named custom-speech-to-text.The fully qualified container image name is, mcr.microsoft.com/azure-cognitive-services/speechservices/custom-speech-to-text. Either append a specific version or append :latest to get the most recent version.VersionPathLatestmcr.microsoft.com/azure-cognitive-services/speechservices/custom-speech-to-text:latest4.12.0mcr.microsoft.com/azure-cognitive-services/speechservices/custom-speech-to-text:4.12.0-amd64All tags, except for latest, are in the following format and are case sensitive:..--NoteThe locale and voice for custom speech to text containers is determined by the custom model ingested by the container.The tags are also available in JSON format for your convenience. The body includes the container path and list of tags. The tags aren't sorted by version, but "latest" is always included at the end of the list as shown in this snippet:{ "name": "azure-cognitive-services/speechservices/custom-speech-to-text", "tags": [ "4.4.0-amd64", "4.5.0-amd64", "4.6.0-amd64", "4.7.0-amd64", "4.8.0-amd64", "4.9.0-amd64", "4.10.0-amd64", "4.11.0-amd64", "4.12.0-amd64", "latest" ]}Get the container image with docker pullYou need the prerequisites including required hardware. Also see the recommended allocation of resources for each Speech container.Use the docker pull command to download a container image from Microsoft Container Registry:docker pull mcr.microsoft.com/azure-cognitive-services/speechservices/custom-speech-to-text:latestNoteThe locale and voice for custom Speech

Example, to download a rescoring display model, you can use the following command with the RescoreId parameter:docker run --rm -it \mcr.microsoft.com/azure-cognitive-services/speechservices/custom-speech-to-text \RescoreId={RESCORE_MODEL_ID} \ Eula=accept \Billing={ENDPOINT_URI} \ApiKey={API_KEY}NoteIf you set more than one query or download parameter, the command will prioritize in this order: BaseModelLocale, model ID, and then DisplayLocale (only applicable for display models).Run the container with docker runUse the docker run command to run the container for service.Custom speech to textDisconnected custom speech to textThe following table represents the various docker run parameters and their corresponding descriptions:ParameterDescription{VOLUME_MOUNT}The host computer volume mount, which Docker uses to persist the custom model. An example is c:\CustomSpeech where the c:\ drive is located on the host machine.{MODEL_ID}The custom speech or base model ID. For more information, see Get the model ID.{ENDPOINT_URI}The endpoint is required for metering and billing. For more information, see billing arguments.{API_KEY}The API key is required. For more information, see billing arguments.When you run the custom speech to text container, configure the port, memory, and CPU according to the custom speech to text container requirements and recommendations.Here's an example docker run command with placeholder values. You must specify the VOLUME_MOUNT, MODEL_ID, ENDPOINT_URI, and API_KEY values:docker run --rm -it -p 5000:5000 --memory 8g --cpus 4 \-v {VOLUME_MOUNT}:/usr/local/models \mcr.microsoft.com/azure-cognitive-services/speechservices/custom-speech-to-text \ModelId={MODEL_ID} \Eula=accept \Billing={ENDPOINT_URI} \ApiKey={API_KEY}This command:Runs a custom speech to text container from the container image.Allocates 4 CPU cores and 8 GB of memory.Loads the custom speech to text model from the volume input mount, for example, C:\CustomSpeech.Exposes TCP port 5000 and allocates a pseudo-TTY for the container.Downloads the model given the ModelId (if not found on the volume mount).If the custom model was previously downloaded, the ModelId is ignored.Automatically removes the container after it exits. The container image is still available on the host computer.For more information about docker run with Speech containers, see Install

And run Speech containers with Docker.To run disconnected containers (not connected to the internet), you must submit this request form and wait for approval. For more information about applying and purchasing a commitment plan to use containers in disconnected environments, see Use containers in disconnected environments in the Azure AI services documentation.If you are approved to run the container disconnected from the internet, the following example shows the formatting of the docker run command to use, with placeholder values. Replace these placeholder values with your own values.In order to prepare and configure a disconnected custom speech to text container, you need two separate speech resources:A regular Azure AI Speech resource that is either configured to use a "S0 - Standard" pricing tier or a "Speech to Text (Custom)" commitment tier pricing plan. This is used to train, download, and configure your custom speech models for use in your container.An Azure AI Speech resource that is configured to use the "DC0 Commitment (Disconnected)" pricing plan. This is used to download your disconnected container license file required to run the container in disconnected mode.Follow these steps to download and run the container in disconnected environments.Download a model for the disconnected container. For this step, use a regular Azure AI Speech resource that is either configured to use a "S0 - Standard" pricing tier or a "Speech to Text (Custom)" commitment tier pricing plan.Download the disconnected container license. For this step, use an Azure AI Speech resource that is configured to use the "DC0 Commitment (Disconnected)" pricing plan.Run the disconnected container for service. For this step, use an Azure AI Speech resource that is configured to use the "DC0 Commitment (Disconnected)" pricing plan.Download a model for the disconnected containerFor this step, use a regular Azure AI Speech resource that is either configured to