Instructions to use hfvladkon/bert_token_classification_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfvladkon/bert_token_classification_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hfvladkon/bert_token_classification_detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hfvladkon/bert_token_classification_detector") model = AutoModelForTokenClassification.from_pretrained("hfvladkon/bert_token_classification_detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download qwen_tokenizer/tokenizer.json from hfvladkon/bert_token_classification_detector: direct link, hf CLI and curl.
- Browser
- Download file 12.8 MB
-
https://huggingface.co/hfvladkon/bert_token_classification_detector/resolve/main/qwen_tokenizer/tokenizer.json
- Command line
-
hf download hf://hfvladkon/bert_token_classification_detector/qwen_tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hfvladkon/bert_token_classification_detector/resolve/main/qwen_tokenizer/tokenizer.json
12.8 MB
- Xet hash:
- ddca7e708ff0da8902fdcef5209d5eea8bf922715733eb02f93026a37478e426
- Size of remote file:
- 12.8 MB
- SHA256:
- 0997f410c57a1f4e53b09e4be8f4a172d90edd9564368fb0847030937229b9f3
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