Instructions to use google-bert/bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-uncased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Splitting text into paragraphs based on shifts of meaning
#47 opened about 3 years ago
by
drmeir
Calculate probability of word after a sentence.
#45 opened about 3 years ago
by
manoj-media-net
Add Core ML conversion
#44 opened about 3 years ago
by
velyan
How to use transformer to match a text paragraph to existing categories description?
2
#37 opened over 3 years ago
by
hsuwill
Adding `safetensors` variant of this model
#34 opened over 3 years ago
by
paulzhang
a tiny miss in exampls
👍 1
#21 opened over 3 years ago
by
sudo
Trying to understand the output of bert-base-uncased for sentiment classification task
#14 opened almost 4 years ago
by
naina79000tyagi
How to I fine tune this model?
👍❤️ 3
7
#12 opened almost 4 years ago
by
ethanjyx
Set dropout probability
#7 opened almost 4 years ago
by
Oleguer
add parameter count?
👍 4
1
#6 opened almost 4 years ago
by
buio
ERROR when inference on gpu
#5 opened almost 4 years ago
by
rikka
Error: "Some weights of the model checkpoint were not used"
3
#4 opened almost 4 years ago
by
EvokerKing
Load model in Keras or Tensorflow and as part of custom model without install transformers?
1
#3 opened about 4 years ago
by
cheyc
Multi-token masks?
7
#1 opened over 4 years ago
by
latitude