Instructions to use VMware/electra-large-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/electra-large-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/electra-large-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/electra-large-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/electra-large-mrqa") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (c74743a370e9a1e21704018996980a8075b32304)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:159a10cd8a910f6f7245e4bdb03bf82a61bd2d87bc7e6e26d16ace95ab8b5afa
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size 1336429528
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