Join 📕📗 Text Classification# 🎛️ Fine-tune a SetFit model using the ArgillaTrainer MLOps Steps: Training NLP Tasks: Text Classification Libraries: SetFit Techniques: few-shot ✨ Add zero-shot suggestions using SetFit MLOps Steps: Labelling NLP Tasks: Text Classification Libraries: SetFit Techniques: zero-shot 📸 Bulk Labelling Multimodal Data MLOps Steps: Labelling NLP Tasks: TextClassification (images) Libraries: Argilla, sentence-transformers Techniques: Semantic search 🔫 Zero-shot and few-shot classification with SetFit MLOps Steps: Labelling, Training NLP Tasks: TextClassification Libraries: setfit, sentence transformers Techniques: Few-shot 💨 Speed-up data labelling with Sentence Transformer embeddings MLOps Steps: Labelling NLP Tasks: TextClassification Libraries: Argilla, sentence-transformers Techniques: Semantic search Monitoring Inference Predictions FastAPI MLOps Steps: Deploying, Monitoring NLP Tasks: TextClassification, TokenClassification (NER) Libraries: spaCy, FastAPI, transformers 💡 Building and testing a zero-shot sentiment classifier with GPT-3 and Argilla MLOps Steps: Labelling NLP Tasks: TextClassification Libraries: OpenAI Techniques: Few-shot, Explainability Argilla with Active Learning and a free Colab GPU MLOps Steps: Deploying, Training NLP Tasks: TextClassification Libraries: Google Colab, small-text Techniques: Active Learning 🔁 Using modAL for Active Learning MLOps Steps: Training NLP Tasks: TextClassification Libraries: modAL Techniques: Active Learning 📰 Building a news classifier with weak supervision MLOps Steps: Labelling NLP Tasks: TextClassification (news) Libraries: Argilla, snorkel, sklearn Techniques: Weak Supervision 🗂 Weak supervision in multi-label text classification tasks MLOps Steps: Labelling, Training NLP Tasks: TextClassification (multi-label) Libraries: Argilla, scikit-multilearn Techniques: Weak Supervision 🧐 Find label errors with cleanlab MLOps Steps: Training, Monitoring NLP Tasks: TextClassification Libraries: cleanlab Techniques: explainability 🕵️♀️ Analyzing predictions with model explainability methods MLOps Steps: Monitoring NLP Tasks: TextClassification Libraries: shap, transformers-interpret Techniques: Explainability 🧼 Clean labels using your model loss MLOps Steps: Monitoring NLP Tasks: TextClassification Libraries: Argilla, transformers Techniques: Explainability 🧱 Extending weak supervision workflows with sentence embeddings MLOps Steps: Labelling, Training NLP Tasks: TextClassification Libraries: Argilla, sentence-transformers Techniques: Weak Supervision 🤯 Few-shot classification with SetFit and a custom dataset MLOps Steps: Labelling, Training NLP Tasks: TextClassification Libraries: setfit Techniques: Few-shot 🤯 Build a custom sentiment classifier with SetFit and Argilla MLOps Steps: Training NLP Tasks: TextClassification (sentiment) Libraries: setfit Techniques: Few-shot 👂 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 🏷️ Label your data to fine-tune a classifier with Hugging Face MLOps Steps: Labelling, Training NLP Tasks: TextClassification (sentiment) Libraries: transformers Techniques: basics 🔁 Using modAL for Active Learning MLOps Steps: Training NLP Tasks: TextClassification Libraries: modAL Techniques: Active Learning 🥇 Compare Text Classification Models MLOps Steps: Monitoring NLP Tasks: TextClassification Libraries: Argilla, SetFit Techniques: Zero-shot classification
