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
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README.md
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language:
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tags:
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license: apache-2.0
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datasets:
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- go_emotions
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"0":"admiration"
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"1":"amusement"
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"27":"neutral"
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language:
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license: apache-2.0
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datasets:
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- go_emotions
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