Instructions to use connectivity/bert_ft_qqp-92 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-92 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-92")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-92") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-92", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-92: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-92/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-92/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-92/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- fdbba7e3064df515714395dd5a8857eab274eab4966a734099e075794c86431d
- Size of remote file:
- 438 MB
- SHA256:
- 846332d0633f8d56e2abec0b2c8c58397de862200398019147baddc16db6bc8a
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