Instructions to use dwisaji/SentimentBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dwisaji/SentimentBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dwisaji/SentimentBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dwisaji/SentimentBert") model = AutoModelForSequenceClassification.from_pretrained("dwisaji/SentimentBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
19452e4 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:24b4ad974cd94c255221b55abdf00fb09f52798f6e266961029ea48f8e89ea34
size 442549613
|