Instructions to use connectivity/bert_ft_qqp-62 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-62 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-62")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-62") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-62", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-62: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-62/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-62/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-62/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 38c706e6800126ec8a071672bac451596bc7d5ee6fdc006ecec520b4e9fc55d7
- Size of remote file:
- 438 MB
- SHA256:
- d476d4c59ca659f72235eda179ce56b2e44a5b321e3439cb4287b08ac057abc5
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