Text Classification
Transformers
PyTorch
Tigrinya
roberta
Eval Results (legacy)
text-embeddings-inference
Instructions to use fgaim/tiroberta-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fgaim/tiroberta-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fgaim/tiroberta-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fgaim/tiroberta-sentiment") model = AutoModelForSequenceClassification.from_pretrained("fgaim/tiroberta-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1a7c46fc00315c142270393c09cddc8ce77f002a0e0956bde331a9fe6ebb220
- Size of remote file:
- 499 MB
- SHA256:
- 671f19b794640f14230d88608afc347e8bc8fd9e2459c846ef60b6c5dccf812d
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