Chalk alternatives and similar packages
Based on the "Science and Data Analysis" category.
Alternatively, view Chalk alternatives based on common mentions on social networks and blogs.
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BigDL
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, DeepSeek, Mixtral, Gemma, Phi, MiniCPM, Qwen-VL, MiniCPM-V, etc.) on Intel XPU (e.g., local PC with iGPU and NPU, discrete GPU such as Arc, Flex and Max); seamlessly integrate with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, vLLM, DeepSpeed, Axolotl, etc. -
Zeppelin
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more. -
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FACTORIE
FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference. -
ND4S
DISCONTINUED. ND4S: N-Dimensional Arrays for Scala. Scientific Computing a la Numpy. Based on ND4J. -
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Clustering4Ever
C4E, a JVM friendly library written in Scala for both local and distributed (Spark) Clustering. -
rscala
The Scala interpreter is embedded in R and callbacks to R from the embedded interpreter are supported. Conversely, the R interpreter is embedded in Scala. -
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InfluxDB – Built for High-Performance Time Series Workloads
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of Chalk or a related project?
README
Chalk
NOTE: This project is currently dormant with no current prospect for further development. Suggestion: check out OpenNLP or StanfordNLP for the JVM or spaCy for Python. (If anyone would like to do something like spaCy for Scala, that would be fantastic.)
Introduction
Chalk is a library for natural language processing (NLP).
What's inside
The latest stable version is 1.3.2. Changes from the previous release include:
- Initial implementation of functional pipelines for NLP applications, and actor-based pipelines based on those components.
See the CHANGELOG for changes in previous versions.
Using Chalk
In SBT:
libraryDependencies += "org.scalanlp" %% "chalk" % "1.3.0"
In Maven:
<dependency>
<groupId>org.scalanlp</groupId>
<artifactId>chalk</artifactId>
<version>1.3.0</version>
</dependency>
Requirements
- Version 1.6 of the Java 2 SDK (http://java.sun.com)
Configuring your environment variables
Set JAVA_HOME to match the top level directory containing the Java installation you want to use. If you want to be able to use the chalk command line executable, set CHALK_DIR to where you put Chalk, and then add the directory CHALK_DIR/bin to your path.
Building the system from source
Chalk uses SBT (Simple Build Tool) with a standard directory structure. To build Chalk, type (in the CHALK_DIR directory):
$ ./build update compile
This will compile the source files and put them in ./target/classes. If this is your first time running it, you will see messages about Scala being downloaded -- this is fine and expected. Once that is over, the Chalk code will be compiled.
To try out other build targets, do:
$ ./build
To make sure all the tests pass, do:
$ ./build test
Documentation for SBT is at http://www.scala-sbt.org/
Questions or suggestions?
Email Jason Baldridge: [email protected]
Or, create an issue: https://github.com/scalanlp/chalk/issues