Instructions to use 123tarunanand/roberta-base-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 123tarunanand/roberta-base-finetuned with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="123tarunanand/roberta-base-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("123tarunanand/roberta-base-finetuned") model = AutoModelForQuestionAnswering.from_pretrained("123tarunanand/roberta-base-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the adversarialQA config and validation split of adversarial_qa
#6 opened about 3 years ago
by
autoevaluator
Add evaluation results on the adversarialQA config and validation split of adversarial_qa
#5 opened about 3 years ago
by
autoevaluator
Adding `safetensors` variant of this model
#4 opened over 3 years ago
by
SFconvertbot
Add evaluation results on the default config and test split of cuad
1
#3 opened almost 4 years ago
by
autoevaluator
Add evaluation results on the adversarialQA config and validation split of adversarial_qa
#2 opened almost 4 years ago
by
autoevaluator
Add evaluation results on the squad_v2 config of squad_v2
#1 opened about 4 years ago
by
autoevaluator