Instructions to use Nadav/roberta-base-squad-nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nadav/roberta-base-squad-nl 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="Nadav/roberta-base-squad-nl")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Nadav/roberta-base-squad-nl") model = AutoModelForQuestionAnswering.from_pretrained("Nadav/roberta-base-squad-nl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Nadav/roberta-base-squad-nl: direct link, hf CLI and curl.
- Browser
- Download file 465 MB
-
https://huggingface.co/Nadav/roberta-base-squad-nl/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Nadav/roberta-base-squad-nl/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Nadav/roberta-base-squad-nl/resolve/main/pytorch_model.bin
465 MB
- Xet hash:
- 3f52e0d489cf85a763e9c1376a1cecf2a00f0357ca6da4e337661cbfa656a256
- Size of remote file:
- 465 MB
- SHA256:
- 475fa8df5c723f5677df9c683c4af4c8dfa3171622f728872f7e2f529cc836da
路
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