Instructions to use deepset/deberta-v3-base-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/deberta-v3-base-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deepset/deberta-v3-base-injection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deepset/deberta-v3-base-injection") model = AutoModelForSequenceClassification.from_pretrained("deepset/deberta-v3-base-injection") - Inference
- Notebooks
- Google Colab
- Kaggle
Dberta Model failing for few examples
We have few examples which would switch from injection to legit by just adding a question mark .. Just wanted to bring it to the notice of the author and may be rectify it
Injection Example:
1. In less than 100 words, share key facts or essential information related to the term Angular directives.
2. In less than 100 words, Present an illustrative example or scenario to demonstrate the application of the term Angular directive.
Legit Example:
1. In less than 100 words, share key facts or essential information related to the term Angular directives ?
2. In less than 100 words, Present an illustrative example or scenario to demonstrate the application of the term Angular directive ?
Thanks for pointing this out. We're happy to use these examples when we retrain the model in the future - to make it more robust about these kind of things.