Instructions to use connectivity/bert_ft_qqp-85 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-85 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-85")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-85") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-85", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-85: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-85/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-85/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-85/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 843e7e05aebcc0d6c71066506e9b2e3121e5cac39e24c463e302562d3e34128c
- Size of remote file:
- 438 MB
- SHA256:
- 4e25a01aa0d7f1a0cf7f6dbbb3b21568665fc3f41b433a9456eeb222d49a6d74
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