Instructions to use izaitova/ner_cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use izaitova/ner_cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="izaitova/ner_cs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("izaitova/ner_cs") model = AutoModelForTokenClassification.from_pretrained("izaitova/ner_cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from izaitova/ner_cs: direct link, hf CLI and curl.
- Browser
- Download file 4.46 kB
-
https://huggingface.co/izaitova/ner_cs/resolve/main/training_args.bin
- Command line
-
hf download hf://izaitova/ner_cs/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/izaitova/ner_cs/resolve/main/training_args.bin
4.46 kB
- Xet hash:
- ada85495b188707ae5d4f23775d9b2e5e809cf613a92a499c1a4d93fa8138798
- Size of remote file:
- 4.46 kB
- SHA256:
- 714e5adfc96f7008267a78babff0b5202b6ecad8b84e16257493bfadab873722
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