Token Classification
Transformers
Safetensors
Spanish
English
Portuguese
modernbert
name-splitting
ner
names
Eval Results (legacy)
Instructions to use ittailup/tori2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ittailup/tori2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ittailup/tori2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ittailup/tori2") model = AutoModelForTokenClassification.from_pretrained("ittailup/tori2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c33cb2c8b05742d7763c265070496b6841ec90efdad146deb67bc9bb274f1cb
- Size of remote file:
- 5.2 kB
- SHA256:
- a55eca196b9f82fe21e7379724d1e1ae2ce2d9a486a14fdbb63bd3617f1d565e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.