Instructions to use connectivity/bert_ft_qqp-15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-15 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-15")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-15") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-15", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-15: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-15/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-15/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-15/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 3f48693027cc0d7bd6db16f3e55610a4149165ccf01d5e8ef6246180a895cb17
- Size of remote file:
- 438 MB
- SHA256:
- 200f83319facad3385d7419e131dff38d8dce4240375a72a97e9766625ee633c
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