Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use smerchi/darija_test3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smerchi/darija_test3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smerchi/darija_test3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smerchi/darija_test3") model = AutoModelForSequenceClassification.from_pretrained("smerchi/darija_test3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 930c6ce1d3098f27dbccf173ad2cfe2723108469fc29f2dc90cd777145a95e4a
- Size of remote file:
- 541 MB
- SHA256:
- 9b07041ef4029d02a29fe630477fd816e36f4e18ed609296d8a7388c37c484ba
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