Feature Extraction
Transformers
PyTorch
TensorFlow
bert
generated_from_keras_callback
dpr
text-embeddings-inference
Instructions to use nlpconnect/dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpconnect/dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nlpconnect/dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nlpconnect/dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2") model = AutoModel.from_pretrained("nlpconnect/dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened almost 3 years ago
by
SFconvertbot