Instructions to use mrm8488/spanbert-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/spanbert-finetuned-squadv2 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="mrm8488/spanbert-finetuned-squadv2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/spanbert-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/spanbert-finetuned-squadv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from mrm8488/spanbert-finetuned-squadv2: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/mrm8488/spanbert-finetuned-squadv2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://mrm8488/spanbert-finetuned-squadv2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/mrm8488/spanbert-finetuned-squadv2/resolve/main/flax_model.msgpack
431 MB
- Xet hash:
- 7af3449767bfd7846c74b3ef02b3d70a5e1322cf094a5c61cb875a785a5882cb
- Size of remote file:
- 431 MB
- SHA256:
- 2232e461f9ee3cede2d028b6b87b9951b4fda75fef088fbbfbab39c73fad64fa
路
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