Word Vector Model Reader (legacy)

This node reads word vector models of different formats:

KNIME - Models previously saved by the Word Vector Writer Node.
Text - Models in standard text format (file ending may be .txt or .csv). Each row contains the word in the first column and the vector in the following columns with the following properties:
Column separator: single whitespace (multiple whitespace, tab and comma are not supported)
Decimal separator: dot
Binary - Compressed or uncompressed binary model like the well known Google News Vectors model (file ending should be .bin.gz).

Note that for external model formats (Text or Binary) only Word2Vec models are supported. Some compatible pretrained Word2Vec models are the following:

Google News Vectors Note: Very large model, may take some time to read.
GloVe Note: These models are in text format and need to be extracted first.

This node can access a variety of different file systems. More information about file handling in KNIME can be found in the official File Handling Guide.

The KNIME Deeplearning4J Integration has been marked as legacy with KNIME Analytics Platform 5.0 and will be deprecated in a future version. If you are using this extension in a production workflow, consider switching to one of the other deep learning integrations available in KNIME Analytics Platform.

Options

Read from

Select a file system which stores the model you want to read. There are four default file system options to choose from:

Local File System: Allows you to select a file from your local system.
Mountpoint: Allows you to read from a mountpoint. When selected, a new drop-down menu appears to choose the mountpoint. Unconnected mountpoints are greyed out but can still be selected (note that browsing is disabled in this case). Go to the KNIME Explorer and connect to the mountpoint to enable browsing. A mountpoint is displayed in red if it was previously selected but is no longer available. You won't be able to save the dialog as long as you don't select a valid i.e. known mountpoint.
Relative to: Allows you to choose whether to resolve the path relative to the current mountpoint, current workflow or the current workflow's data area. When selected a new drop-down menu appears to choose which of the three options to use.
Custom/KNIME URL: Allows to specify a URL (e.g. file://, http:// or knime:// protocol). When selected, a spinner appears that allows you to specify the desired connection and read timeout in milliseconds. In case it takes longer to connect to the host / read the file, the node fails to execute. Browsing is disabled for this option.

It is possible to use other file systems with this node. Therefore, you have to enable the file system connection input port of this node by clicking the ... in the bottom left corner of the node's icon and choose Add File System Connection port .
Afterwards, you can simply connect the desired connector node to this node. The file system connection will then be shown in the drop-down menu.

File/URL

Enter a URL when reading from Custom/KNIME URL, otherwise enter a path to a file. The required syntax of a path depends on the chosen file system, such as "C:\path\to\file" (Local File System on Windows) or "/path/to/file" (Local File System on Linux/MacOS and Mountpoint). For file systems connected via input port, the node description of the respective connector node describes the required path format. You can also choose a previously selected file from the drop-down list, or select a location from the "Browse..." dialog. Note that browsing is disabled in some cases:

Custom/KNIME URL: Browsing is always disabled.
Mountpoint: Browsing is disabled if the selected mountpoint isn't connected. Go to the KNIME Explorer and connect to the mountpoint to enable browsing.
File systems provided via input port: Browsing is disabled if the connector node hasn't been executed since the workflow has been opened. (Re)execute the connector node to enable browsing.

The location can be exposed as or automatically set via a path flow variable.

Input Ports

…: The file system connection.

Output Ports

: The loaded model.

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Installation

To use this node in KNIME, install the extension KNIME Textprocessing - Deeplearning4J Integration (64bit only) (legacy) from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202312081534

On NodePit since: 2024-07-09

Last update: 2024-11-15

KNIME versions: Since v4.2

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