Instructions to use HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi") model = AutoModelForSequenceClassification.from_pretrained("HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 299848b9c6dfa2b8cff0eea5a61f5429b367232686adf0e684d691fa6cf81bc0
- Size of remote file:
- 651 MB
- SHA256:
- a5c5fbc7271c88e273ff6bd94cb844ca7e080628a0c41b05f4a97765645e6be0
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