Instructions to use DeepPavlov/bert-base-multilingual-cased-sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepPavlov/bert-base-multilingual-cased-sentence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DeepPavlov/bert-base-multilingual-cased-sentence")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/bert-base-multilingual-cased-sentence") model = AutoModel.from_pretrained("DeepPavlov/bert-base-multilingual-cased-sentence") - Notebooks
- Google Colab
- Kaggle
Adding ONNX file of this model
#3 opened about 1 year ago
by
sergeyshaykhullin
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot
Update README.md
#1 opened almost 4 years ago
by
lbourdois