Instructions to use noahjadallah/cause-effect-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noahjadallah/cause-effect-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="noahjadallah/cause-effect-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("noahjadallah/cause-effect-detection") model = AutoModelForTokenClassification.from_pretrained("noahjadallah/cause-effect-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from noahjadallah/cause-effect-detection: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/noahjadallah/cause-effect-detection/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://noahjadallah/cause-effect-detection/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/noahjadallah/cause-effect-detection/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 7c4c4ff6716e5a38e4e36af16056d3b26915abd8a5322827901e9fc39ec8a9fe
- Size of remote file:
- 436 MB
- SHA256:
- 4102bd192eb9063279b672c3da22d96e7b481897d8988f307f570f345078405e
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