Instructions to use Akash751/banglabert-code-mixed-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akash751/banglabert-code-mixed-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Akash751/banglabert-code-mixed-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Akash751/banglabert-code-mixed-emotion") model = AutoModelForSequenceClassification.from_pretrained("Akash751/banglabert-code-mixed-emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4609bf8f8718f5a53b3276684c4614c24102bfa9f335dcd31458cfa6c5175fa5
- Size of remote file:
- 1.38 kB
- SHA256:
- abca19c7924f8ff1cf998f27b8070560d3ac3af3d49fdf83800d25fa71b124ea
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