Instructions to use universalner/uner_ser_set with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_ser_set with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_ser_set")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_ser_set") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_ser_set", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from universalner/uner_ser_set: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/universalner/uner_ser_set/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://universalner/uner_ser_set/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/universalner/uner_ser_set/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- 6e5ca015bc2239bee29fc12664f5e32ce392f309328bfad377ca7692bc7ed114
- Size of remote file:
- 2.24 GB
- SHA256:
- e7f82502ddf6d82a856d461b156c2c7a4554ab30b385d51abc6e8cc50bdb8194
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