Instructions to use clhuang/albert-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clhuang/albert-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clhuang/albert-sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clhuang/albert-sentiment") model = AutoModelForSequenceClassification.from_pretrained("clhuang/albert-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("clhuang/bert-sentiment")
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model = AutoModelForSequenceClassification.from_pretrained("
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## Pediction
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target_names=['Negative','Positive']
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("clhuang/bert-sentiment")
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model = AutoModelForSequenceClassification.from_pretrained("clhuang/bert-sentiment")
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## Pediction
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target_names=['Negative','Positive']
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