Text Classification
Transformers
PyTorch
Arabic
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use MMars/camelbert-mix_flodusta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMars/camelbert-mix_flodusta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MMars/camelbert-mix_flodusta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MMars/camelbert-mix_flodusta") model = AutoModelForSequenceClassification.from_pretrained("MMars/camelbert-mix_flodusta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1aad261944e8d8c1e79c32514d41a4b0eccf5241fad1c2ccad17d7d683e6e38c
- Size of remote file:
- 436 MB
- SHA256:
- 9137f5eb119dff07f21ef9218c94f0da189c25e7bc1872ddd86431264440b161
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