Instructions to use PragmaticMachineLearning/price-norm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PragmaticMachineLearning/price-norm with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PragmaticMachineLearning/price-norm") model = AutoModelForSeq2SeqLM.from_pretrained("PragmaticMachineLearning/price-norm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41ab377b7693ed6908e9e6d23cf5d0de69ba55abfea10dbe72871b0b5f92a080
- Size of remote file:
- 1.2 GB
- SHA256:
- 72b5027d2d6241297c89faa77f1ded649dd4cfb8a2acce1ee3bd7d07598aae9d
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