Instructions to use VMware/tinyroberta-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/tinyroberta-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/tinyroberta-mrqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/tinyroberta-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/tinyroberta-mrqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from VMware/tinyroberta-mrqa: direct link, hf CLI and curl.
- Browser
- Download file 326 MB
-
https://huggingface.co/VMware/tinyroberta-mrqa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://VMware/tinyroberta-mrqa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/VMware/tinyroberta-mrqa/resolve/main/pytorch_model.bin
326 MB
- Xet hash:
- 050cdec201d6aafb52b35afaf89714a9df5073e90080897365bafcf86233dc8e
- Size of remote file:
- 326 MB
- SHA256:
- d9da1cc685984a61dec5bb5a370a254bb59b09a278590b24f7ca6fc682a50fb1
路
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