Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use Ftmhd/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ftmhd/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ftmhd/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ftmhd/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("Ftmhd/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 141354a469ee2c008ffc27e1432bd225c958bde7f18b4fcf53db0ff8e4ebdbff
- Size of remote file:
- 568 MB
- SHA256:
- 32fca18ce4d47516c74d24989b31a111990c51a24b0e8d7e833c483509da5c4b
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