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 model.safetensors from VMware/roberta-base-mrqa: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/VMware/roberta-base-mrqa/resolve/main/model.safetensors
- Command line
-
hf download hf://VMware/roberta-base-mrqa/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/VMware/roberta-base-mrqa/resolve/main/model.safetensors
496 MB
- Xet hash:
- 0eeab6716e94386a56fec4a39c77cf9c2455432da92701a95eb706948ad5f654
- Size of remote file:
- 496 MB
- SHA256:
- 8e5f534d01019f5360e24c530697a33fd69eb772ff197622307bf940ad1221a1
路
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