Instructions to use poom-sci/bert-base-uncased-multi-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poom-sci/bert-base-uncased-multi-emotion with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="poom-sci/bert-base-uncased-multi-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poom-sci/bert-base-uncased-multi-emotion") model = AutoModelForSequenceClassification.from_pretrained("poom-sci/bert-base-uncased-multi-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b7b6372dc4a56d5f1e420d5a8d92aa1d896b95690dda9b90e4d5ddd4ad73306
- Size of remote file:
- 438 MB
- SHA256:
- 577c0081b5b6a397d7638cd949637c99f55938f80cdbe6def18ff6ec72b01b8d
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