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92 changes: 46 additions & 46 deletions docs/source/guide/ml_tutorials.html
Original file line number Diff line number Diff line change
Expand Up @@ -5,37 +5,37 @@
- Segmentation
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/timeseries.png
image: /guide/ml_tutorials/timeseries.png
meta_description: Tutorial demonstrating a minimal ML backend that performs time series segmentation in Label Studio.
meta_title: Time Series Segmenter for Label Studio
order: 35
tier: all
title: Time Series Segmenter for Label Studio
type: guide
url: /tutorials/timeseries_segmenter.html
url: /guide/ml_tutorials/timeseries_segmenter.html
- categories:
- Natural Language Processing
- Text Classification
- BERT
- Hugging Face
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/bert.png
image: /guide/ml_tutorials/bert.png
meta_description: Tutorial on how to use BERT-based text classification with your
Label Studio project
meta_title: BERT-based text classification
order: 35
tier: all
title: Classify text with a BERT model
type: guide
url: /tutorials/bert_classifier.html
url: /guide/ml_tutorials/bert_classifier.html
- categories:
- Computer Vision
- Optical Character Recognition
- EasyOCR
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/easyocr.png
image: /guide/ml_tutorials/easyocr.png
meta_description: The EasyOCR model connection integrates the capabilities of EasyOCR
with Label Studio to assist in machine learning labeling tasks involving Optical
Character Recognition (OCR).
Expand All @@ -44,21 +44,21 @@
tier: all
title: Transcribe text from images with EasyOCR
type: guide
url: /tutorials/easyocr.html
url: /guide/ml_tutorials/easyocr.html
- categories:
- Natural Language Processing
- Named Entity Recognition
- Flair
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/flair.png
image: /guide/ml_tutorials/flair.png
meta_description: Tutorial on how to use Label Studio and Flair for faster NER labeling
meta_title: Use Flair with Label Studio
order: 75
tier: all
title: NER labeling with Flair
type: guide
url: /tutorials/flair.html
url: /guide/ml_tutorials/flair.html
- categories:
- Natural Language Processing
- Named Entity Recognition
Expand All @@ -67,31 +67,31 @@
- Hugging Face
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/gliner.png
image: /guide/ml_tutorials/gliner.png
meta_description: Tutorial on how to use GLiNER with your Label Studio project to
complete NER tasks
meta_title: Use GLiNER for NER annotation
order: 37
tier: all
title: Use GLiNER for NER annotation
type: guide
url: /tutorials/gliner.html
url: /guide/ml_tutorials/gliner.html
- categories:
- Computer Vision
- Image Annotation
- Object Detection
- Grounding DINO
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/grounding-dino.png
image: /guide/ml_tutorials/grounding-dino.png
meta_description: Label Studio tutorial for using Grounding DINO for zero-shot object
detection in images
meta_title: Image segmentation in Label Studio using a Grounding DINO backend
order: 15
tier: all
title: Zero-shot object detection and image segmentation with Grounding DINO
type: guide
url: /tutorials/grounding_dino.html
url: /guide/ml_tutorials/grounding_dino.html
- categories:
- Computer Vision
- Image Annotation
Expand All @@ -101,7 +101,7 @@
- Segment Anything Model
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/grounding-sam.png
image: /guide/ml_tutorials/grounding-sam.png
meta_description: Label Studio tutorial for using Grounding DINO and SAM for zero-shot
object detection in images
meta_title: Image segmentation in Label Studio using a Grounding DINO backend and
Expand All @@ -111,15 +111,15 @@
title: Zero-shot object detection and image segmentation with Grounding DINO and
SAM
type: guide
url: /tutorials/grounding_sam.html
url: /guide/ml_tutorials/grounding_sam.html
- categories:
- Generative AI
- Large Language Model
- Text Generation
- Hugging Face
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/hf-llm.png
image: /guide/ml_tutorials/hf-llm.png
meta_description: This tutorial explains how to run Hugging Face Large Language
model backend in Label Studio. Hugging Face Large Language Model Backend is a
machine learning backend designed to work with Label Studio, providing a custom
Expand All @@ -129,37 +129,37 @@
tier: all
title: Hugging Face Large Language Model (LLM)
type: guide
url: /tutorials/huggingface_llm.html
url: /guide/ml_tutorials/huggingface_llm.html
- categories:
- Natural Language Processing
- Named Entity Recognition
- Hugging Face
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/hf-ner.png
image: /guide/ml_tutorials/hf-ner.png
meta_description: This tutorial explains how to run a Hugging Face NER backend in
Label Studio.
meta_title: Label Studio tutorial to run Hugging Face NER backend
order: 25
tier: all
title: Hugging Face NER
type: guide
url: /tutorials/huggingface_ner.html
url: /guide/ml_tutorials/huggingface_ner.html
- categories:
- Natural Language Processing
- Named Entity Recognition
- Interactive matching
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/interactive-substring-matching.png
image: /guide/ml_tutorials/interactive-substring-matching.png
meta_description: Use the interactive substring matching model for labeling NER
tasks in Label Studio
meta_title: Interactive substring matching for NER tasks
order: 30
tier: all
title: Interactive substring matching for NER tasks
type: guide
url: /tutorials/interactive_substring_matching.html
url: /guide/ml_tutorials/interactive_substring_matching.html
- categories:
- Generative AI
- Retrieval Augmented Generation
Expand All @@ -168,15 +168,15 @@
- Langchain
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/langchain.png
image: /guide/ml_tutorials/langchain.png
meta_description: Use Langchain, OpenAI, and Google to generate responses based
on Google search results.
meta_title: RAG with a Langchain search agent
order: 45
tier: all
title: RAG with a Langchain search agent
type: guide
url: /tutorials/langchain_search_agent.html
url: /guide/ml_tutorials/langchain_search_agent.html
- categories:
- Generative AI
- Large Language Model
Expand All @@ -186,15 +186,15 @@
- ChatGPT
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/llm-interactive.png
image: /guide/ml_tutorials/llm-interactive.png
meta_description: Label Studio tutorial for interactive LLM labeling with OpenAI,
Azure, or Ollama
meta_title: Interactive LLM labeling with OpenAI, Azure, or Ollama
order: 5
tier: all
title: Interactive LLM labeling with GPT
type: guide
url: /tutorials/llm_interactive.html
url: /guide/ml_tutorials/llm_interactive.html
- categories:
- Computer Vision
- Object Detection
Expand All @@ -203,59 +203,59 @@
- MMDetection
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/openmmlab.png
image: /guide/ml_tutorials/openmmlab.png
meta_description: This is a tutorial on how to use the example MMDetection model
backend with Label Studio for image segmentation tasks.
meta_title: Object detection in images with Label Studio and MMDetection
order: 65
tier: all
title: Object detection with bounding boxes using MMDetection
type: guide
url: /tutorials/mmdetection-3.html
url: /guide/ml_tutorials/mmdetection-3.html
- categories:
- Audio/Speech Processing
- Automatic Speech Recognition
- NeMo
- NVidia
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/nvidia.png
image: /guide/ml_tutorials/nvidia.png
meta_description: Tutorial on how to use set up Nvidia NeMo to use for ASR tasks
in Label Studio
meta_title: Automatic Speech Recognition with NeMo
order: 60
tier: all
title: Automatic Speech Recognition with NVidia NeMo
type: guide
url: /tutorials/nemo_asr.html
url: /guide/ml_tutorials/nemo_asr.html
- categories:
- Computer Vision
- Image Annotation
- Object Detection
- Segment Anything Model
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/sam2-images.png
image: /guide/ml_tutorials/sam2-images.png
meta_title: Using SAM2 with Label Studio for Image Annotation
order: 15
tier: all
title: SAM2 with Images
type: guide
url: /tutorials/segment_anything_2_image.html
url: /guide/ml_tutorials/segment_anything_2_image.html
- categories:
- Computer Vision
- Video Annotation
- Object Detection
- Segment Anything Model
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/sam2-video.png
image: /guide/ml_tutorials/sam2-video.png
meta_title: Using SAM2 with Label Studio for Video Annotation
order: 15
tier: all
title: SAM2 with Videos
type: guide
url: /tutorials/segment_anything_2_video.html
url: /guide/ml_tutorials/segment_anything_2_video.html
- categories:
- Computer Vision
- Object Detection
Expand All @@ -265,105 +265,105 @@
- ONNX
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/segment-anything.png
image: /guide/ml_tutorials/segment-anything.png
meta_description: Label Studio tutorial for labeling images with MobileSAM or ONNX
SAM.
meta_title: Interactive annotation in Label Studio with Segment Anything Model (SAM)
order: 10
tier: all
title: Interactive annotation with Segment Anything Model
type: guide
url: /tutorials/segment_anything_model.html
url: /guide/ml_tutorials/segment_anything_model.html
- categories:
- Natural Language Processing
- Text Classification
- Scikit-learn
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/scikit-learn.png
image: /guide/ml_tutorials/scikit-learn.png
meta_description: Tutorial on how to use an example ML backend for Label Studio
with Scikit-learn logistic regression
meta_title: Sklearn Text Classifier model for Label Studio
order: 50
tier: all
title: Sklearn Text Classifier model
type: guide
url: /tutorials/sklearn_text_classifier.html
url: /guide/ml_tutorials/sklearn_text_classifier.html
- categories:
- Natural Language Processing
- Named Entity Recognition
- SpaCy
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/spacy.png
image: /guide/ml_tutorials/spacy.png
meta_description: Tutorial on how to use Label Studio and spaCy for faster NER and
POS labeling
meta_title: Use spaCy models with Label Studio
order: 70
tier: all
title: spaCy models for NER
type: guide
url: /tutorials/spacy.html
url: /guide/ml_tutorials/spacy.html
- categories:
- Computer Vision
- Optical Character Recognition
- Tesseract
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/tesseract.png
image: /guide/ml_tutorials/tesseract.png
meta_description: Tutorial for how to use Label Studio and Tesseract to assist with
your OCR projects
meta_title: Interactive bounding boxes OCR in Label Studio with a Tesseract backend
order: 55
tier: all
title: Interactive bounding boxes OCR with Tesseract
type: guide
url: /tutorials/tesseract.html
url: /guide/ml_tutorials/tesseract.html
- categories:
- Generative AI
- Large Language Model
- WatsonX
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/watsonx.png
image: /guide/ml_tutorials/watsonx.png
meta_title: Integrate WatsonX with Label Studio
order: 15
tier: all
title: Integrate WatsonX with Label Studio
type: guide
url: /tutorials/watsonx_llm.html
url: /guide/ml_tutorials/watsonx_llm.html
- categories:
- Computer Vision
- Object Detection
- Image Segmentation
- YOLO
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/yolo.png
image: /guide/ml_tutorials/yolo.png
meta_description: Tutorial on how to use an example ML backend for Label Studio
with YOLO
meta_title: YOLO ML Backend for Label Studio
order: 50
tier: all
title: YOLO ML Backend for Label Studio
type: guide
url: /tutorials/yolo.html
url: /guide/ml_tutorials/yolo.html
- categories:
- Computer Vision
- Video Classification
- Temporal Labeling
- LSTM
hide_frontmatter_title: true
hide_menu: true
image: /tutorials/yolo-video-classification.png
image: /guide/ml_tutorials/yolo-video-classification.png
meta_description: Tutorial on how to use an example ML backend for Label Studio
with TimelineLabels
meta_title: TimelineLabels ML Backend for Label Studio
order: 51
tier: all
title: TimelineLabels ML Backend for Label Studio
type: guide
url: /tutorials/yolo_timeline_labels.html
url: /guide/ml_tutorials/yolo_timeline_labels.html
layout: templates
meta_description: Tutorial documentation for setting up a machine learning model with
predictions using PyTorch, GPT2, Sci-kit learn, and other popular frameworks.
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