Instructions to use connectivity/bert_ft_qqp-11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-11")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-11") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-11: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-11/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-11/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-11/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 7740b27b9deb4f87e0af061c9a24cddb4213dc30b4c01c16f218c942ad4d41ef
- Size of remote file:
- 438 MB
- SHA256:
- 252119aa2a44dc18f540a83d5d176634b46bee225d1544fc1ec5b4dad1bf40ac
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