πŸ’ͺ🏽 Training#

πŸŽ›οΈ Fine-tune a SetFit model using the ArgillaTrainer

MLOps Steps: Training
NLP Tasks: Text Classification
Libraries: SetFit
Techniques: few-shot

πŸ”« Zero-shot and few-shot classification with SetFit

MLOps Steps: Labelling, Training
NLP Tasks: TextClassification
Libraries: setfit, sentence transformers
Techniques: Few-shot

πŸ•ΈοΈ Train a summarization model with Unstructured and Transformers

MLOps Steps: Labelling, Training
NLP Tasks: TextGeneration
Libraries: unstructured, transformers
Techniques: basics

🀯 Build a custom sentiment classifier with SetFit and Argilla

MLOps Steps: Training
NLP Tasks: TextClassification (sentiment)
Libraries: setfit
Techniques: Few-shot

πŸ‘‚ Active learning for text classification with small-text

MLOps Steps: Training
NLP Tasks: TextClassification
Libraries: small-text
Techniques: Active Learning

✨ Fast active learning using classy-classification

MLOps Steps: Training
NLP Tasks: TextClassification
Libraries: classy-classification
Techniques: Few-shot, Active Learning

🀯 Few-shot classification with SetFit and a custom dataset

MLOps Steps: Labelling, Training
NLP Tasks: TextClassification
Libraries: setfit
Techniques: Few-shot

🧱 Extending weak supervision workflows with sentence embeddings

MLOps Steps: Labelling, Training
NLP Tasks: TextClassification
Libraries: Argilla, sentence-transformers
Techniques: Weak Supervision

🧐 Find label errors with cleanlab

MLOps Steps: Training, Monitoring
NLP Tasks: TextClassification
Libraries: cleanlab
Techniques: explainability

🏷️ Label your data to fine-tune a classifier with Hugging Face

MLOps Steps: Labelling, Training
NLP Tasks: TextClassification (sentiment)
Libraries: transformers
Techniques: basics

🐭 Weakly supervised NER with skweak

MLOps Steps: Labelling, Training
NLP Tasks: TokenClassification (NER)
Libraries: Argilla, skweak
Techniques: Weak Supervision

πŸ—‚ Weak supervision in multi-label text classification tasks

MLOps Steps: Labelling, Training
NLP Tasks: TextClassification (multi-label)
Libraries: Argilla, scikit-multilearn
Techniques: Weak Supervision

πŸ” Using modAL for Active Learning

MLOps Steps: Training
NLP Tasks: TextClassification
Libraries: modAL
Techniques: Active Learning