Instructions to use b3x0m/bert-xomlac-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use b3x0m/bert-xomlac-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="b3x0m/bert-xomlac-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("b3x0m/bert-xomlac-ner") model = AutoModelForTokenClassification.from_pretrained("b3x0m/bert-xomlac-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
9502a03
1
Parent(s): 0d22d95
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (aa7a80fe5b9f4c1d3e784ce84d30dc8d9bb77c1a)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:857f5c71866ab382f8806227e199c66598f568cce726448c119c95ffd8836fe9
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size 406781860
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