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
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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
| 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 | |
| # nerx2 | |