Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use JasperLS/deberta-v3-base-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JasperLS/deberta-v3-base-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JasperLS/deberta-v3-base-injection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JasperLS/deberta-v3-base-injection") model = AutoModelForSequenceClassification.from_pretrained("JasperLS/deberta-v3-base-injection") - Notebooks
- Google Colab
- Kaggle
Commit ·
0ca59bf
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Parent(s): 0282f06
Librarian Bot: Add base_model information to model (#4)
Browse files- Librarian Bot: Add base_model information to model (dec1672d53c491840f43f0dff8d67fce49567a2a)
Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>
README.md
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: deberta-v3-base-injection
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results: []
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- generated_from_trainer
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metrics:
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- accuracy
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base_model: microsoft/deberta-v3-base
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model-index:
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- name: deberta-v3-base-injection
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results: []
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