Instructions to use VMware/roberta-base-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/roberta-base-mrqa 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="VMware/roberta-base-mrqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/roberta-base-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/roberta-base-mrqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from VMware/roberta-base-mrqa: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/VMware/roberta-base-mrqa/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://VMware/roberta-base-mrqa@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/VMware/roberta-base-mrqa/resolve/refs%2Fpr%2F1/pytorch_model.bin
496 MB
- Xet hash:
- a4f687622b6356a64bc6221949bb3188123bad1a9484d6f48c94fc44e4d3d584
- Size of remote file:
- 496 MB
- SHA256:
- eddc74f3bfe45b60652b972963702b0d37ebc76ef99a12740056e224d2530a40
路
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