Instructions to use connectivity/bert_ft_qqp-24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-24")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-24") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-24: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-24/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-24/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-24/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- a29d17dc41747546470c8a32b18deae4a9d154d62d95f48810c6227a1854eacb
- Size of remote file:
- 438 MB
- SHA256:
- 203e6b69563167dd1633a46d27413ee5d20ce77f34935df397764da8732922d6
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