# Accessing images

Learn how to access images in the Speechmatics Container system

The Speechmatics Docker images are obtained from the Speechmatics Docker Repository. If you do not have a Speechmatics Docker Repository account or have lost your details, please reach out to [Support](https://support.speechmatics.com).

The latest information about the Containers can be found in the knowledge base section of the [Support Portal](https://support.speechmatics.com). If a support account is not available or the *Containers* section is not visible in the Support Portal, please reach out to [Support](https://support.speechmatics.com) for help.

## Prerequisites[​](#prerequisites "Direct link to Prerequisites")

* Speechmatics Docker repository credentials – speak to [Support](https://support.speechmatics.com) to get these
* Language Code – the ISO language code (for example `fr` for French)
* `LICENSE_TOKEN` - The value of the signed claims token which is used to validate the license file. This is required to run the Container. Speechmatics Support will provide this within the license file generated for each customer
* `TAG` – which is used to identify the image version

## Docker repository login[​](#docker-repository-login "Direct link to Docker repository login")

Using the credentials supplied by Speechmatics, login to our Docker repository:

```
docker login https://speechmaticspublic.azurecr.io
```

You will be prompted for your username and password that was provided to you. If successful, you will see the response:

```
Login Succeeded
```

If unsuccessful, please verify your credentials and URL. If problems persist, please contact Speechmatics Support.

Speechmatics require all customers to cache a copy of the Docker image(s) within their own environment. Once the first version of the container is pulled from the Speechmatics Software Repository, please re-host in a private container registry instead and reference your personal registry in your deployments.

## Pulling core speech CPU images[​](#pulling-core-speech-cpu-images "Direct link to Pulling core speech CPU images")

Each supported language pack comes as a different Docker image, so the process will need to be repeated for each language pack required using the relevant language code.

```
# pulling Batch Global English (en) with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/batch-asr-transcriber-en:15.19.0

# pulling the Batch Spanish (es) model with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/batch-asr-transcriber-es:15.19.0

# pulling Realtime Global English (en) with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/rt-asr-transcriber-en:15.19.0
```

See [how to run the Core Speech CPU container here.](/deployments/container/cpu-speech-to-text.md)

## Pulling transcription GPU images[​](#pulling-transcription-gpu-images "Direct link to Pulling transcription GPU images")

The Transcription GPU images are required to use the most accurate models.

See [how to run the Transcription GPU container here.](/deployments/container/gpu-speech-to-text.md)

To access additional language configurations for containers, please [speak to our Support Team](https://support.speechmatics.com).

### Standard model[​](#standard-model "Direct link to Standard model")

There is a single image available that supports all languages for the Standard model. There are language specific images available that support the Enhanced and Standard models.

```
# pulling the Standard model Transcription GPU inference server which supports all languages with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/sm-gpu-inference-server-standard-all:15.19.0

# pulling language specific Transcription GPU inference servers available for en, es, de, fr. Supports both Enhanced and Standard models with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/sm-gpu-inference-server-en:15.19.0
```

### Enhanced model[​](#enhanced-model "Direct link to Enhanced model")

Depending on which Enhanced model languages are required, you can pull specific images.

Language Pack 1

Bashkir, Basque, Belarusian, English, Esperanto, Irish, Malay & English bilingual, Mandarin & English bilingual, Mandarin Malay Tamil & English multilingual, Marathi, Mongolian, Tamil, Tamil & English bilingual, Turkish, Ukrainian, Uyghur, Welsh

```
docker pull speechmaticspublic.azurecr.io/sm-gpu-inference-server-enhanced-recipe1:15.19.0 
```

Language Pack 2

Bulgarian, Croatian, Estonian, Galician, Indonesian, Interlingua, Latvian, Lithuanian, Persian, Romanian, Slovakian, Slovenian, Spanish, Tagalog, Urdu

```
docker pull speechmaticspublic.azurecr.io/sm-gpu-inference-server-enhanced-recipe2:15.19.0 
```

Language Pack 3

Arabic & English bilingual, Catalan, Czech, Danish, Finnish, German, Greek, Hebrew, Hindi, Hungarian, Italian, Korean, Malay, Swahili, Swedish

```
docker pull speechmaticspublic.azurecr.io/sm-gpu-inference-server-enhanced-recipe3:15.19.0 
```

Language Pack 4

Arabic, Bengali, Cantonese, Dutch, French, Japanese, Maltese, Mandarin, Norwegian, Polish, Portuguese, Russian, Thai, Vietnamese

```
docker pull speechmaticspublic.azurecr.io/sm-gpu-inference-server-enhanced-recipe4:15.19.0 
```

### Standard and Enhanced model[​](#standard-and-enhanced-model "Direct link to Standard and Enhanced model")

A single image supports all languages for both the Standard and Enhanced models, so you do not need to pull individual language pack images. The `sm-gpu-inference-server-standard-all` image above covers all languages for the Standard model only.

```
# pulling the Transcription GPU inference server supporting all languages for both Enhanced and Standard models with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/sm-gpu-inference-server-all-lang:15.19.0
```

This image contains both models. To load only one of them, see [Running only one model](/deployments/container/gpu-speech-to-text.md#running-only-one-model). To load only some of the image's languages, see [Loading only selected languages](/deployments/container/gpu-speech-to-text.md#loading-only-selected-languages).

### Melia 1 model[​](#melia-1-model "Direct link to Melia 1 model")

Melia 1 is a multilingual, GPU-only model, generally available in Batch, with Real-time (streaming) available as an early preview. For an overview, see [Models](/speech-to-text/models.md#melia-1).

```
# pulling the Melia 1 Batch transcriber with the 1.3.0 tag:
docker pull speechmaticspublic.azurecr.io/sm-asr-transcriber-melia-1:1.3.0

# pulling the Melia 1 GPU inference server with the 1.3.0 tag:
docker pull speechmaticspublic.azurecr.io/sm-asr-inference-server-melia-1:1.3.0
```

See [how to run the Melia 1 GPU container here.](/deployments/container/gpu-speech-to-text-melia-1.md)

## Pulling translation GPU image[​](#pulling-translation-gpu-image "Direct link to Pulling translation GPU image")

This GPU image is required to use Translation in Batch or Realtime.

```
# pulling the Translation GPU inference server which supports all translation pairs with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/sm-translation-inference-server:15.19.0
```

See [how to run the Translation GPU container here.](/deployments/container/gpu-translation.md)

## Pulling bilingual images[​](#pulling-bilingual-images "Direct link to Pulling bilingual images")

To use Spanish and English bilingual transcription you need to pull the Core Speech CPU image below for the client and use the Spanish [GPU Inference Server](#pulling-transcription-gpu-images).

```
# pulling Batch bilingual Spanish and English with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/batch-asr-transcriber-es-bilingual-en:15.19.0

# pulling Realtime bilingual Spanish and English with the 15.19.0 tag:
docker pull speechmaticspublic.azurecr.io/rt-asr-transcriber-es-bilingual-en:15.19.0
```

Bilingual is only available for GPU deployments. Batch and Realtime are supported.

## Pulling language ID Image[​](#pulling-language-id-image "Direct link to Pulling language ID Image")

This image is required to use Language ID.

```
# pulling the latest Language ID image:
docker pull speechmaticspublic.azurecr.io/langid:2.2.1
```

See [how to run the Language ID container here.](/deployments/container/language-id.md)