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sentiment analysis using DJL / published by https://github.com/dacr/code-examples-manager #65caa624-232d-483d-83d2-0d4ea0067540/99eda85629f074ad954edb56d281dded3cf70db3
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// 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 $file | |
// --------------------- | |
//> using scala "3.3.1" | |
//> using dep "org.slf4j:slf4j-api:2.0.11" | |
//> using dep "org.slf4j:slf4j-simple:2.0.11" | |
//> using dep "net.java.dev.jna:jna:5.14.0" | |
//> using dep "ai.djl:api:0.26.0" | |
//> using dep "ai.djl:basicdataset:0.26.0" | |
//> using dep "ai.djl:model-zoo:0.26.0" | |
//> using dep "ai.djl.huggingface:tokenizers:0.26.0" | |
//> using dep "ai.djl.mxnet:mxnet-engine:0.26.0" | |
//> using dep "ai.djl.mxnet:mxnet-model-zoo:0.26.0" | |
//> using dep "ai.djl.pytorch:pytorch-engine:0.26.0" | |
//> using dep "ai.djl.pytorch:pytorch-model-zoo:0.26.0" | |
//> using dep "ai.djl.tensorflow:tensorflow-engine:0.26.0" | |
//> using dep "ai.djl.tensorflow:tensorflow-model-zoo:0.26.0" | |
//> using dep "ai.djl.paddlepaddle:paddlepaddle-engine:0.26.0" | |
//> using dep "ai.djl.paddlepaddle:paddlepaddle-model-zoo:0.26.0" | |
//> using dep "ai.djl.onnxruntime:onnxruntime-engine:0.26.0" | |
// --------------------- | |
System.setProperty("org.slf4j.simpleLogger.defaultLogLevel", "error") | |
import ai.djl.Application | |
import ai.djl.engine.Engine | |
import ai.djl.modality.Classifications | |
import ai.djl.repository.zoo.Criteria | |
import ai.djl.training.util.ProgressBar | |
import ai.djl.huggingface.translator.{TextClassificationTranslatorFactory, TextEmbeddingTranslatorFactory} | |
import scala.io.AnsiColor.{BLUE, BOLD, CYAN, GREEN, MAGENTA, RED, RESET, UNDERLINED, YELLOW} | |
val criteria = | |
Criteria.builder | |
.setTypes(classOf[String], classOf[Classifications]) | |
.optModelUrls("djl://ai.djl.huggingface.pytorch/distilbert-base-uncased-finetuned-sst-2-english") | |
.optEngine("PyTorch") | |
.optTranslatorFactory(new TextClassificationTranslatorFactory) | |
.optProgress(new ProgressBar) | |
.build | |
val model = criteria.loadModel() | |
val predictor = model.newPredictor() | |
def analyze(text: String): Unit = { | |
println(s"${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") |
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