Token Classification
Transformers
TensorBoard
Safetensors
bert
semantic-role-labeling
Generated from Trainer
Instructions to use pakkinlau/bert-base-uncased-finetuned-advanced-srl_arg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pakkinlau/bert-base-uncased-finetuned-advanced-srl_arg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pakkinlau/bert-base-uncased-finetuned-advanced-srl_arg")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pakkinlau/bert-base-uncased-finetuned-advanced-srl_arg") model = AutoModelForTokenClassification.from_pretrained("pakkinlau/bert-base-uncased-finetuned-advanced-srl_arg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
base_model: dannashao/bert-base-uncased-finetuned-advanced-srl_arg
duplicated_from: dannashao/bert-base-uncased-finetuned-advanced-srl_arg
pipeline_tag: token-classification
library_name: transformers
tags:
- transformers
- semantic-role-labeling
- generated_from_trainer
model_index:
- name: SRL (UPropBank dev)
results:
- task:
type: semantic-role-labeling
name: SRL
metrics:
- type: f1
value: 0.8669
name: F1
original_sha: 7e13b4f
pakkinlau/bert-base-uncased-finetuned-advanced-srl_arg
This repository is an archival mirror ofdannashao/bert-base-uncased-finetuned-advanced-srl_arg.
Weights and tokenizer are byte‑identical to upstream commit 7e13b4f.
Only the hosting namespace has changed to guarantee long‑term availability for my other ongoing research project.
Maintainer · Pak Kin Lau