Instructions to use ka05ar/banglabert-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ka05ar/banglabert-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ka05ar/banglabert-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ka05ar/banglabert-sentiment") model = AutoModelForSequenceClassification.from_pretrained("ka05ar/banglabert-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a502ddf140ce0a964e581e9cebd3175fa0887e7f4e0b5a2b57fc47b7a52262aa
- Size of remote file:
- 443 MB
- SHA256:
- cb12ba4a91a13f459a13e74a21d4b7ba843996c5e5cd5db3a395dea7b900f570
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