Instructions to use HausaNLP/AfriSenti with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HausaNLP/AfriSenti with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HausaNLP/AfriSenti")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("HausaNLP/AfriSenti") model = AutoModel.from_pretrained("HausaNLP/AfriSenti") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 706c1bcd776e3fa057476029012c9f3657130b9c399b2c239fda519c17e6b42b
- Size of remote file:
- 2.24 GB
- SHA256:
- f605b7684c100c472052578f5b8700b12377088c76fb33e0c9d4944ecfe1edb3
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