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Fine-Tuning Llama 3: Adapting LLMs for Specialized Domains 🚀
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Computer Vision
Semantic Segmentation with Polygons
Semantic Segmentation with Masks
Object Detection with Bounding Boxes
Keypoint Labeling
Image Captioning
Optical Character Recognition (OCR)
Image Classification
Visual Question Answering
Object Detection with Ellipses
Multi-Image Classification
Inventory Tracking
Visual Genome
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Question Answering
Sentiment Analysis Text Classification
Named Entity Recognition
Taxonomy
Relation Extraction
Text Summarization
Machine Translation
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Automatic Speech Recognition
Sound Event Detection
Automatic Speech Recognition using Segments
Signal Quality Detection
Speaker Diarization
Dialogue Analysis
Intent Classification
Audio Classification
Contextual Scrolling
Audio Classification with Segments
Voice Activity Detection
Conversational AI
Response Generation
Response Selection
Coreference Resolution and Entity Linking
Slot Filling and Intent Classification
Ranking and Scoring
Pairwise Regression
Document Retrieval
Pairwise Classification
Content-based Image Retrieval
Website Rating
ASR Hypotheses Selection
Text-to-Image Generation
Search Page Ranking
Visual Ranker
Structured Data Parsing
Freeform Metadata
PDF Classification
Tabular Data
HTML Entity Recognition
HTML Classification
Time Series Analysis
Time Series Forecasting
Change Point Detection
Activity Recognition
Signal Quality
Outliers and Anomaly Detection
Time Series Classification
Time Series Labeling
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Video Classification
Video Timeline Segmentation
Video Object Detection and Tracking
LLM Fine-tuning
Supervised LLM Fine-Tuning
Human Preferences collection for RLHF
RAG Retrieval
LLM Evaluations
LLM Response Moderation
LLM Response Grading
Side-by-Side LLM Output Comparison
Evaluate RAG with Human Feedback
Evaluate RAG with Ragas
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Video Classification
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