Instructions to use VMware/electra-base-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/electra-base-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/electra-base-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/electra-base-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/electra-base-mrqa") - Notebooks
- Google Colab
- Kaggle
Commit 路
47f07f9
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Parent(s): 09716b1
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (d8760f16747f8d5365ad88ea51611e57fabb9352)
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 sha256:58b0c25ccb2871abc6d23b7b594c253955941854944258f9675bb12d0b4805fe
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size 435600872
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