Instructions to use connectivity/bert_ft_qqp-72 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-72 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-72")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-72") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-72", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-72: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-72/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-72/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-72/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 2921953ba64fb43ecd610d7acd8992ffa5caf571f83b196fced11c287b3ef34f
- Size of remote file:
- 438 MB
- SHA256:
- afd28944ae43465480c858d28949182ddf1bf3b675a3c562229cbeecaa03d492
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