Instructions to use edithram23/Redaction_personal_info with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edithram23/Redaction_personal_info with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edithram23/Redaction_personal_info")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edithram23/Redaction_personal_info") model = AutoModelForSequenceClassification.from_pretrained("edithram23/Redaction_personal_info", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from edithram23/Redaction_personal_info: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/edithram23/Redaction_personal_info/resolve/main/training_args.bin
- Command line
-
hf download hf://edithram23/Redaction_personal_info/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/edithram23/Redaction_personal_info/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 1d3243677288217f05cea4aeb167672fb6757d23177b2c45dcfd895960c9eb33
- Size of remote file:
- 5.24 kB
- SHA256:
- 522e1d1c64170c5a8e8052a1ee3925b8e6a8bc3d5f20f0b716a52785290af1c9
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