Instructions to use connectivity/bert_ft_qqp-93 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-93 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-93")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-93") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-93", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-93: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-93/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-93/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-93/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 3c2f029281fc3783f7519086a7df2d430308ce492249678d9446c799d733c236
- Size of remote file:
- 438 MB
- SHA256:
- 779bc5ef8d14f50a36804dd672144278b5f7fafee63024a55d8c44caae2200bc
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