Instructions to use argv947059/example-based-ner-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use argv947059/example-based-ner-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="argv947059/example-based-ner-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("argv947059/example-based-ner-bert") model = AutoModel.from_pretrained("argv947059/example-based-ner-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from argv947059/example-based-ner-bert: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
-
https://huggingface.co/argv947059/example-based-ner-bert/resolve/main/added_tokens.json
- Command line
-
hf download hf://argv947059/example-based-ner-bert/added_tokens.json
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curl -L -o added_tokens.json https://huggingface.co/argv947059/example-based-ner-bert/resolve/main/added_tokens.json
28 Bytes
| {"<s>": 30522, "<e>": 30523} |