Instructions to use BDRC/Bo-Tsawa-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BDRC/Bo-Tsawa-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BDRC/Bo-Tsawa-Detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BDRC/Bo-Tsawa-Detection") model = AutoModelForTokenClassification.from_pretrained("BDRC/Bo-Tsawa-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BDRC/Bo-Tsawa-Detection: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/BDRC/Bo-Tsawa-Detection/resolve/main/training_args.bin
- Command line
-
hf download hf://BDRC/Bo-Tsawa-Detection/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BDRC/Bo-Tsawa-Detection/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- 59db3c6c7283d827490e35b15b10c1e09278a2673e895cd31e391a0e96883477
- Size of remote file:
- 5.27 kB
- SHA256:
- be9be02a006eefd79d86ac0438675c37f17dc51c777bd38d53a6ae386a9f0a19
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