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:
- cff9cc15e06179331738f7b2a7ec24151068d963d2f09dbb7e5b12738ac5515b
- Size of remote file:
- 2.86 kB
- SHA256:
- 39b8b79de313c824b1e224a8a479abdcef92953b2cfcd0880074ff8f9d39f93b
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