Instructions to use MaiiaCompsolutions/title_pair_clf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaiiaCompsolutions/title_pair_clf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MaiiaCompsolutions/title_pair_clf")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MaiiaCompsolutions/title_pair_clf") model = AutoModelForSequenceClassification.from_pretrained("MaiiaCompsolutions/title_pair_clf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MaiiaCompsolutions/title_pair_clf: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/MaiiaCompsolutions/title_pair_clf/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MaiiaCompsolutions/title_pair_clf/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MaiiaCompsolutions/title_pair_clf/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 27f7413f1b4ba6f97b6cab46262fbd4645d21d69177b5480e35e30f1af5c92eb
- Size of remote file:
- 438 MB
- SHA256:
- 1c2d003fd8ca0004f508e17c2a3a625c53297c6602f525dac8a9e8021ed8210d
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