Token Classification
Transformers
PyTorch
TensorFlow
JAX
Rust
ONNX
Safetensors
English
bert
Eval Results (legacy)
Instructions to use mdizak/bert-large-NER-rust with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mdizak/bert-large-NER-rust with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mdizak/bert-large-NER-rust")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mdizak/bert-large-NER-rust") model = AutoModelForTokenClassification.from_pretrained("mdizak/bert-large-NER-rust") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
786494d | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:d63d39520929bbeab16344157582be46f09a3ab43095b14f1b1586636a50f171
size 1330169528
|