Instructions to use connectivity/bert_ft_qqp-89 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-89 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-89")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-89") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-89", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-89: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-89/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-89/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-89/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 49d343d112e6a3ab8f2b70e2c7321244f1c7b047195ad5547ab9baa9d7b65155
- Size of remote file:
- 438 MB
- SHA256:
- 070464c3c5ceeb616e81d4e27c63c7bddf037478ed1b83e99d5232244d1aeb24
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