Instructions to use Jeevesh8/bert_ft_qqp-21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-21")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-21") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeevesh8/bert_ft_qqp-21: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Jeevesh8/bert_ft_qqp-21/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeevesh8/bert_ft_qqp-21/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeevesh8/bert_ft_qqp-21/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 8bd4a94c2aa8e4223ad9167a1e26350fa9eb9ca53664e3f10cd4110ad31d2be3
- Size of remote file:
- 438 MB
- SHA256:
- 100208d41b27b361ed42265b07d8db52da6b16e647b997613cda03462ed781d2
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