google-research/bert

Health v2 · maintenance only

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40046 stars · 9678 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Google Research's official TensorFlow implementation of BERT, the Bidirectional Encoder Representations from Transformers language model, along with pre-trained model checkpoints. It provides code for pre-training and fine-tuning BERT on NLP tasks like question answering, sentence classification, and language inference.

Use cases

• fine-tune BERT for text classification
• download pre-trained BERT checkpoints
• train a question answering model on SQuAD
• run NLP experiments with TensorFlow
• use small BERT models for limited compute
• pre-train a transformer language model from scratch

When to choose

• you need the original reference BERT implementation in TensorFlow
• you want official pre-trained checkpoints including compact models
• you are reproducing the BERT paper's GLUE or SQuAD results

When to avoid

• you prefer PyTorch or Hugging Face Transformers ecosystem
• you need generative or decoder-based LLMs
• you want actively developed features and recent model architectures

Facets

library · maturity maintenance

machine-learning nlp deep-learning transformers machine-learning deep-learning python bert pretrained-models tensorflow language-model fine-tuning google-research natural-language-processing gpu

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