Instructions to use connectivity/bert_ft_qqp-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-6") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-6: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-6/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-6/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- d4b65e18ad18cbddcb6e0cef5476602cf3999697fb840f62c340c47efaca0a23
- Size of remote file:
- 438 MB
- SHA256:
- 4ec9f3ca1a7f5e884ff271960a26658228faf0099ca364b94196e92c7d4da6e6
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