Instructions to use connectivity/bert_ft_qqp-66 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-66 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-66")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-66") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-66", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-66: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-66/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-66/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-66/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- bd93d168a92eef6c753723e78e78a8028fd07c1e2e1e0de3b65c02cbd908d34c
- Size of remote file:
- 438 MB
- SHA256:
- 9d2723e68c7beabc79e5895c68b55f2327fccec542bae7024408bac284eaff28
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