Instructions to use ashishraics/deberta_v3_large_mlm_feedback_prize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashishraics/deberta_v3_large_mlm_feedback_prize with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ashishraics/deberta_v3_large_mlm_feedback_prize")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ashishraics/deberta_v3_large_mlm_feedback_prize") model = AutoModel.from_pretrained("ashishraics/deberta_v3_large_mlm_feedback_prize") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
This Model can be used in the Kaggle Competition - https://www.kaggle.com/competitions/feedback-prize-effectivenes Data Used to train the MLM model - https://www.kaggle.com/competitions/feedback-prize-2021
- Downloads last month
- 3