Skip to content

Instantly share code, notes, and snippets.

@dacr
Last active May 25, 2024 10:19
sentiment analysis using DJL / published by https://github.com/dacr/code-examples-manager #65caa624-232d-483d-83d2-0d4ea0067540/4d079d819834510a709ae96a96f636d28e6b9df7
// summary : sentiment analysis using DJL
// keywords : djl, machine-learning, tutorial, sentiment, ai, @testable
// publish : gist
// authors : David Crosson
// license : Apache NON-AI License Version 2.0 (https://raw.githubusercontent.com/non-ai-licenses/non-ai-licenses/main/NON-AI-APACHE2)
// id : 65caa624-232d-483d-83d2-0d4ea0067540
// created-on : 2024-01-28T16:16:23+01:00
// managed-by : https://github.com/dacr/code-examples-manager
// run-with : scala-cli $file
// ---------------------
//> using scala "3.4.2"
//> using dep "org.slf4j:slf4j-api:2.0.13"
//> using dep "org.slf4j:slf4j-simple:2.0.13"
//> using dep "net.java.dev.jna:jna:5.14.0"
//> using dep "ai.djl:api:0.28.0"
//> using dep "ai.djl:basicdataset:0.28.0"
//> using dep "ai.djl:model-zoo:0.28.0"
//> using dep "ai.djl.huggingface:tokenizers:0.28.0"
//> using dep "ai.djl.mxnet:mxnet-engine:0.28.0"
//> using dep "ai.djl.mxnet:mxnet-model-zoo:0.28.0"
//> using dep "ai.djl.pytorch:pytorch-engine:0.28.0"
//> using dep "ai.djl.pytorch:pytorch-model-zoo:0.28.0"
//> using dep "ai.djl.tensorflow:tensorflow-engine:0.28.0"
//> using dep "ai.djl.tensorflow:tensorflow-model-zoo:0.28.0"
////> using dep "ai.djl.paddlepaddle:paddlepaddle-engine:0.28.0"
////> using dep "ai.djl.paddlepaddle:paddlepaddle-model-zoo:0.28.0"
//> using dep "ai.djl.onnxruntime:onnxruntime-engine:0.28.0"
// ---------------------
System.setProperty("org.slf4j.simpleLogger.defaultLogLevel", "error")
import ai.djl.Application
import ai.djl.engine.Engine
import ai.djl.modality.Classifications
import ai.djl.repository.zoo.Criteria
import ai.djl.training.util.ProgressBar
import ai.djl.huggingface.translator.{TextClassificationTranslatorFactory, TextEmbeddingTranslatorFactory}
import scala.io.AnsiColor.{BLUE, BOLD, CYAN, GREEN, MAGENTA, RED, RESET, UNDERLINED, YELLOW}
val criteria =
Criteria.builder
.setTypes(classOf[String], classOf[Classifications])
.optModelUrls("djl://ai.djl.huggingface.pytorch/distilbert-base-uncased-finetuned-sst-2-english")
.optEngine("PyTorch")
.optTranslatorFactory(new TextClassificationTranslatorFactory)
.optProgress(new ProgressBar)
.build
val model = criteria.loadModel()
val predictor = model.newPredictor()
def analyze(text: String): Unit = {
println(s"${GREEN}====================$text====================${RESET}")
val result = predictor.predict(text)
println(result)
}
analyze("Hello world")
analyze("I like you")
analyze("This an awful shirt")
analyze("You are a fucking bastard")
analyze("This is not very good for you but it can help")
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment