Instructions to use connectivity/bert_ft_qqp-88 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-88 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-88")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-88") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-88", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-88: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-88/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-88/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-88/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 96e203753cdc00395453141248eaddcd71228bbeee676bdd4ffa1c29895ee572
- Size of remote file:
- 438 MB
- SHA256:
- b0ae2fd1e15e9de31b4c3a9da7534930c151d5d852a96fcc642da4c1fc29a70d
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