Text Classification
Transformers
TensorBoard
Safetensors
Amharic
xlm-roberta
amharic
sentiment-analysis
intent-classification
code-switching
ethiopia
adfluence-ai
Eval Results (legacy)
text-embeddings-inference
Instructions to use YosefA/adfluence-intent-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YosefA/adfluence-intent-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YosefA/adfluence-intent-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YosefA/adfluence-intent-model") model = AutoModelForSequenceClassification.from_pretrained("YosefA/adfluence-intent-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78e0207f06be9d76f5db8bce779072abd26598f2bdd31075a0cefdfacf3398b2
- Size of remote file:
- 17.1 MB
- SHA256:
- 3ffb37461c391f096759f4a9bbbc329da0f36952f88bab061fcf84940c022e98
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