Instructions to use savasy/bert-base-turkish-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use savasy/bert-base-turkish-squad 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="savasy/bert-base-turkish-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("savasy/bert-base-turkish-squad") model = AutoModelForQuestionAnswering.from_pretrained("savasy/bert-base-turkish-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from savasy/bert-base-turkish-squad: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/savasy/bert-base-turkish-squad/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://savasy/bert-base-turkish-squad/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/savasy/bert-base-turkish-squad/resolve/main/flax_model.msgpack
440 MB
- Xet hash:
- 37f0164d1b7bdf4a95893281e5ba308ba3a7455abee8bbbabe0faa478d50ba2e
- Size of remote file:
- 440 MB
- SHA256:
- af63bf6cdc1ad4d88a768b9deb29cff5fdcc85b46c9e5e2ba90155ccf7b66e81
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