Text Classification
Transformers
Safetensors
PyTorch
English
bert
sentiment-analysis
healthcare
lifestyle
fine-tuned
Eval Results (legacy)
Instructions to use keanteng/bert-sentiment-wqd7005 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keanteng/bert-sentiment-wqd7005 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keanteng/bert-sentiment-wqd7005")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keanteng/bert-sentiment-wqd7005") model = AutoModelForSequenceClassification.from_pretrained("keanteng/bert-sentiment-wqd7005", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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