Instructions to use slightlycodic/TC-ABB-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slightlycodic/TC-ABB-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="slightlycodic/TC-ABB-BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("slightlycodic/TC-ABB-BERT") model = AutoModelForTokenClassification.from_pretrained("slightlycodic/TC-ABB-BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from slightlycodic/TC-ABB-BERT: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/slightlycodic/TC-ABB-BERT/resolve/main/training_args.bin
- Command line
-
hf download hf://slightlycodic/TC-ABB-BERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/slightlycodic/TC-ABB-BERT/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- f3c90b4e449270309bdfb17e46799d8d5690ad368b467e09c6c3572fe23e2e8e
- Size of remote file:
- 5.3 kB
- SHA256:
- d0cc2ee336532824dc4c8c2c831bc8c809f32e931a82fcd07a01f825d26d2769
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