Join ๐ช๐ฝ Training# ๐ซ Zero-shot and few-shot classification with SetFit MLOps Steps: Labelling, Training NLP Tasks: TextClassification Libraries: setfit, sentence transformers Techniques: Few-shot ๐ธ๏ธ Train a summarization model with Unstructured and Transformers MLOps Steps: Labelling, Training NLP Tasks: TextGeneration Libraries: unstructured, transformers Techniques: basics ๐คฏ Build a custom sentiment classifier with SetFit and Argilla MLOps Steps: Training NLP Tasks: TextClassification (sentiment) Libraries: setfit Techniques: Few-shot ๐ Active learning for text classification with small-text MLOps Steps: Training NLP Tasks: TextClassification Libraries: small-text Techniques: Active Learning โจ Fast active learning using classy-classification MLOps Steps: Training NLP Tasks: TextClassification Libraries: classy-classification Techniques: Few-shot, Active Learning ๐คฏ Few-shot classification with SetFit and a custom dataset MLOps Steps: Labelling, Training NLP Tasks: TextClassification Libraries: setfit Techniques: Few-shot ๐งฑ Extending weak supervision workflows with sentence embeddings MLOps Steps: Labelling, Training NLP Tasks: TextClassification Libraries: Argilla, sentence-transformers Techniques: Weak Supervision ๐ง Find label errors with cleanlab MLOps Steps: Training, Monitoring NLP Tasks: TextClassification Libraries: cleanlab Techniques: explainability ๐ท๏ธ Label your data to fine-tune a classifier with Hugging Face MLOps Steps: Labelling, Training NLP Tasks: TextClassification (sentiment) Libraries: transformers Techniques: basics ๐ญ Weakly supervised NER with skweak MLOps Steps: Labelling, Training NLP Tasks: TokenClassification (NER) Libraries: Argilla, skweak Techniques: Weak Supervision ๐ Weak supervision in multi-label text classification tasks MLOps Steps: Labelling, Training NLP Tasks: TextClassification (multi-label) Libraries: Argilla, scikit-multilearn Techniques: Weak Supervision ๐ Using modAL for Active Learning MLOps Steps: Training NLP Tasks: TextClassification Libraries: modAL Techniques: Active Learning