Instructions to use connectivity/bert_ft_qqp-84 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-84 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-84")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-84") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-84", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-84: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-84/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-84/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-84/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c9d0c80289bcff3518dcad4d4122bda67bdcd526ca07d63dddb0af08a3a76abd
- Size of remote file:
- 438 MB
- SHA256:
- c848ce93b78c36abd300c6d66bc7ace335db3de8c76016a00bab3e75ec486b27
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