Instructions to use TweebankNLP/bertweet-tb2-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TweebankNLP/bertweet-tb2-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TweebankNLP/bertweet-tb2-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("TweebankNLP/bertweet-tb2-ner") model = AutoModelForTokenClassification.from_pretrained("TweebankNLP/bertweet-tb2-ner") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -9,6 +9,7 @@ license: cc-by-nc-4.0
|
|
| 9 |
- In the paper, it is referred as `HuggingFace-BERTweet (TB2)` in the NER table.
|
| 10 |
|
| 11 |
## How to use the model
|
|
|
|
| 12 |
|
| 13 |
```python
|
| 14 |
from transformers import AutoTokenizer, AutoModelForTokenClassification
|
|
|
|
| 9 |
- In the paper, it is referred as `HuggingFace-BERTweet (TB2)` in the NER table.
|
| 10 |
|
| 11 |
## How to use the model
|
| 12 |
+
- **PRE-PROCESSING**: when you apply the model on tweets, please make sure that tweets are preprocessed by the [TweetTokenizer](https://github.com/VinAIResearch/BERTweet/blob/master/TweetNormalizer.py) to get the best performance.
|
| 13 |
|
| 14 |
```python
|
| 15 |
from transformers import AutoTokenizer, AutoModelForTokenClassification
|