Instructions to use bolu61/logsegmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bolu61/logsegmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bolu61/logsegmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bolu61/logsegmenter") model = AutoModelForTokenClassification.from_pretrained("bolu61/logsegmenter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 222cafa0d3627bb07d0bb5d1e30301ac57269e802c3a8752f7de5c555d043b4d
- Size of remote file:
- 5.43 kB
- SHA256:
- 51d90b786efd503489ffbd7769dda4614d710fe6d20ceca8319034eb22deeb33
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