Instructions to use spacemanidol/neuralmagic-bert-squad-12layer-0sparse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spacemanidol/neuralmagic-bert-squad-12layer-0sparse 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="spacemanidol/neuralmagic-bert-squad-12layer-0sparse")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("spacemanidol/neuralmagic-bert-squad-12layer-0sparse") model = AutoModelForQuestionAnswering.from_pretrained("spacemanidol/neuralmagic-bert-squad-12layer-0sparse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from spacemanidol/neuralmagic-bert-squad-12layer-0sparse: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/spacemanidol/neuralmagic-bert-squad-12layer-0sparse/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://spacemanidol/neuralmagic-bert-squad-12layer-0sparse/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/spacemanidol/neuralmagic-bert-squad-12layer-0sparse/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- 5eb03ab8f71c7932e1f1a644ad9a591f8795fdb97dfadfa0afd8471b4ef25b4d
- Size of remote file:
- 436 MB
- SHA256:
- 17f5e07c403cae81fb93061ed38b9aa095e004f08178817ca078e14acf8f18f9
路
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