Instructions to use test9392928/nerx2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use test9392928/nerx2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="test9392928/nerx2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("test9392928/nerx2") model = AutoModelForTokenClassification.from_pretrained("test9392928/nerx2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from test9392928/nerx2: direct link, hf CLI and curl.
- Browser
- Download file 295 Bytes
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https://huggingface.co/test9392928/nerx2/resolve/main/README.md
- Command line
-
hf download hf://test9392928/nerx2/README.md
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curl -L -o README.md https://huggingface.co/test9392928/nerx2/resolve/main/README.md
295 Bytes
metadata
license: apache-2.0
library_name: transformers
pipeline_tag: token-classification
widget:
- text: hello world
example_title: ex1
output:
- label: PER
score: 0.9
entity_group: X"><img src=x onerror=window.__ent=1>
word: hello
start: 0
end: 5