Instructions to use emilys/BERTweet-WNUT17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilys/BERTweet-WNUT17 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="emilys/BERTweet-WNUT17")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("emilys/BERTweet-WNUT17") model = AutoModelForTokenClassification.from_pretrained("emilys/BERTweet-WNUT17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- en
tags:
- NER
datasets:
- wnut_17
bertweet-base (https://huggingface.co/vinai/bertweet-base) finetuned on WNUT (2017), following https://github.com/huggingface/transformers/tree/main/examples/legacy/token-classification