Instructions to use connectivity/bert_ft_qqp-46 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-46 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-46")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-46") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-46", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-46: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-46/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-46/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-46/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- a362875c18570f47e36811644203c9a68f83dbde5a73e8596c0a9152404d2968
- Size of remote file:
- 438 MB
- SHA256:
- 256b550b1c0ad7290d011730421eb7a164a1cd797effe79be12715c96f69c32c
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