Token Classification
Transformers
PyTorch
Safetensors
English
bert
drone
drone forensics
named entity recognition
Instructions to use swardiantara/drone-term-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swardiantara/drone-term-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="swardiantara/drone-term-extractor")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("swardiantara/drone-term-extractor") model = AutoModelForTokenClassification.from_pretrained("swardiantara/drone-term-extractor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f94545ae36f802afe3020d6a52cee389811e9ea0e8da233a2e376ecb2a59e2e
- Size of remote file:
- 431 MB
- SHA256:
- 612247f519016ebff284aba14684e98ba9083dd82c085bc2addd64941e2f3a59
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.