Instructions to use connectivity/bert_ft_qqp-43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-43")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-43") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-43", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-43: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-43/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-43/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-43/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 3310781f7363b786acda6a13f62e6ff020cf8809db85a29e9eea0a9ebd090909
- Size of remote file:
- 438 MB
- SHA256:
- 6ca1d78a8c3d48f27f684e6faf930389077c127a1b6baa51716e2456838d752a
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