Instructions to use DSI/TweetBasedSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DSI/TweetBasedSA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DSI/TweetBasedSA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DSI/TweetBasedSA") model = AutoModelForSequenceClassification.from_pretrained("DSI/TweetBasedSA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
537daa6 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:18472396cfc8b3bc24dbd6c89d445f74e786f676edadcb3fc4af7a493b7c5805
size 651455917
|