Instructions to use Ching/negation_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ching/negation_detector 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="Ching/negation_detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Ching/negation_detector") model = AutoModelForQuestionAnswering.from_pretrained("Ching/negation_detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from Ching/negation_detector: direct link, hf CLI and curl.
- Browser
- Download file 623 Bytes
-
https://huggingface.co/Ching/negation_detector/resolve/main/scheduler.pt
- Command line
-
hf download hf://Ching/negation_detector/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/Ching/negation_detector/resolve/main/scheduler.pt
623 Bytes
- Xet hash:
- f7e60691191252314d033880ec6846fc64db64eaf9549d20832c2e98f342103e
- Size of remote file:
- 623 Bytes
- SHA256:
- d156b72cd60004ef440a876477aa872ad2db804cd53917f06d82aebe1bd3b2d6
路
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