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 checkpoint-375/optimizer.pt from slightlycodic/TC-ABB-BERT: direct link, hf CLI and curl.
- Browser
- Download file 871 MB
-
https://huggingface.co/slightlycodic/TC-ABB-BERT/resolve/main/checkpoint-375/optimizer.pt
- Command line
-
hf download hf://slightlycodic/TC-ABB-BERT/checkpoint-375/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/slightlycodic/TC-ABB-BERT/resolve/main/checkpoint-375/optimizer.pt
871 MB
- Xet hash:
- fc306ad2005c69495a47bdad3430a1e33c67b436cf2ef75a8efbac3dc529477f
- Size of remote file:
- 871 MB
- SHA256:
- a2a333900e9bdc932bb7ae6c3c25412350031f1fb4ca8da601132e6968fc2ff5
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