Instructions to use Jeevesh8/init_bert_ft_qqp-21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-21")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-21") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeevesh8/init_bert_ft_qqp-21: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Jeevesh8/init_bert_ft_qqp-21/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeevesh8/init_bert_ft_qqp-21/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeevesh8/init_bert_ft_qqp-21/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 62defece0fe180e06769b05e039b8407e3bc9903fa189e7268217609e1262197
- Size of remote file:
- 438 MB
- SHA256:
- d8163bd69b37c96867c4856f52df889db20faff559bb089e7e67dd210c7e97e5
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