Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use binh230/deberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binh230/deberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="binh230/deberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("binh230/deberta-base") model = AutoModelForSequenceClassification.from_pretrained("binh230/deberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3608796fe5405d8d49b275a91aa2ef95702f5febef7519bc1f14aaf8734889d
- Size of remote file:
- 5.18 kB
- SHA256:
- cad9b173c796aa11ca90414bc463380c33f0a4efede98d05a98508b9f88ddd99
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