Token Classification
Transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
English
bert
Eval Results (legacy)
Instructions to use dslim/bert-base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dslim/bert-base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dslim/bert-base-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dslim/bert-base-NER") model = AutoModelForTokenClassification.from_pretrained("dslim/bert-base-NER") - Inference
- Notebooks
- Google Colab
- Kaggle
B-LOC and I-LOC
#14
by bobiq - opened
Is there a way to merge entity names into a single one if it contains B-LOC and a few I-LOCs? I get lots of split names such as West Bank as two entities or B iden as two entities as well.
Interested too! Did you find a solution?
NO.
Just solved!
All you need to do is to use the following argument when calling for pipeline:
aggregation_strategy="simple"
Nice. Thanks.
Yay! It worked! It's a project I did a month ago. Just adding it to the pipeline made it work!