Instructions to use PragmaticMachineLearning/name-norm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PragmaticMachineLearning/name-norm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PragmaticMachineLearning/name-norm") model = AutoModelForSeq2SeqLM.from_pretrained("PragmaticMachineLearning/name-norm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from PragmaticMachineLearning/name-norm: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/PragmaticMachineLearning/name-norm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://PragmaticMachineLearning/name-norm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PragmaticMachineLearning/name-norm/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- fb4f862449ddf2c5e11afc85c05a25e551ddbb5864f7400a22a2677e8bc9f3b5
- Size of remote file:
- 1.2 GB
- SHA256:
- e62289648c5cd554de7471be7016740c5bca1b74d0c4dc9685d9e455e89df2b1
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