Text Classification
Transformers
Safetensors
English
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use tom-010/judge_answer___29_deberta_v3_base_msmarco_answerability with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tom-010/judge_answer___29_deberta_v3_base_msmarco_answerability with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tom-010/judge_answer___29_deberta_v3_base_msmarco_answerability")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tom-010/judge_answer___29_deberta_v3_base_msmarco_answerability") model = AutoModelForSequenceClassification.from_pretrained("tom-010/judge_answer___29_deberta_v3_base_msmarco_answerability", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 28000
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model.safetensors
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