Token Classification
Transformers
PyTorch
English
albert
Generated from Trainer
Eval Results (legacy)
Instructions to use Jorgeutd/albert-base-v2-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jorgeutd/albert-base-v2-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jorgeutd/albert-base-v2-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jorgeutd/albert-base-v2-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("Jorgeutd/albert-base-v2-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Align label mapping with conll2003 dataset
#1
by lewtun HF Staff - opened
Hi there, your model is using a default label mapping. Accept this PR to align the label mapping with the conll2003 dataset this model was trained on. This will enable your model to be evaluated by Hugging Face's automatic model evaluator
Jorgeutd changed pull request status to merged