Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use mljn/mdeberta-v3-base-finetuned-econ_frame-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mljn/mdeberta-v3-base-finetuned-econ_frame-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mljn/mdeberta-v3-base-finetuned-econ_frame-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mljn/mdeberta-v3-base-finetuned-econ_frame-classification") model = AutoModelForSequenceClassification.from_pretrained("mljn/mdeberta-v3-base-finetuned-econ_frame-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea160564e5ab34f7d61c1b68e2e9e63cc3d28995d3bf5ebc863dc6f2d8bc5686
- Size of remote file:
- 16.4 MB
- SHA256:
- d5249d92f8d658ed3d19f52a5885b7abbf7f82a90cc18a2b6c7166af54a884f6
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