Instructions to use connectivity/bert_ft_qqp-36 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-36 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-36")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-36") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-36", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-36: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-36/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-36/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-36/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 36926437070891b398ca822976fed6e5715edef6ab43c6d809945a95d5893d30
- Size of remote file:
- 438 MB
- SHA256:
- b2940b0847c6fda4a0552f4753db153125d46763459da60f34a7e9bc7db9addf
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