Instructions to use language-ml-lab/postagger-azb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use language-ml-lab/postagger-azb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="language-ml-lab/postagger-azb")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("language-ml-lab/postagger-azb") model = AutoModelForTokenClassification.from_pretrained("language-ml-lab/postagger-azb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:431397821339c4d29201e2b22a6a75cc82fbdcaca06e893c6d67ba16f64059dd
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size 371207528
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