Instructions to use deepset/xlm-roberta-base-squad2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/xlm-roberta-base-squad2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/xlm-roberta-base-squad2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/xlm-roberta-base-squad2-distilled") model = AutoModelForQuestionAnswering.from_pretrained("deepset/xlm-roberta-base-squad2-distilled", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Add evaluation results on the adversarialQA config of adversarial_qa
Browse filesBeep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\
Your model has been evaluated on the adversarialQA config of the [adversarial_qa](https://huggingface.co/datasets/adversarial_qa) dataset by @ceyda , using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-adversarial_qa-e34332b7-12205627).\
Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=adversarial_qa).\
Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=adversarial_qa).
README.md
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thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
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tags:
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- exbert
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---
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# deepset/xlm-roberta-base-squad2-distilled
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thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
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tags:
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- exbert
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model-index:
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- name: deepset/xlm-roberta-base-squad2-distilled
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results:
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: adversarial_qa
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type: adversarial_qa
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config: adversarialQA
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split: validation
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metrics:
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- name: Exact Match
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type: exact_match
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value: 22.8
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verified: true
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- name: F1
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type: f1
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value: 33.2484
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verified: true
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---
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# deepset/xlm-roberta-base-squad2-distilled
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