Instructions to use Firdania/sindesa-indobert-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Firdania/sindesa-indobert-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Firdania/sindesa-indobert-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Firdania/sindesa-indobert-ner") model = AutoModelForTokenClassification.from_pretrained("Firdania/sindesa-indobert-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 884c13d545a1b0133bbeb8ed92e4418b4afc14a15f74aff82e15d69544b8d4fb
- Size of remote file:
- 5.2 kB
- SHA256:
- 8a3a2894f5c931e243da8552371708519e02284d61b1c595ad0cd7f9502222cd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.