Text Classification
Transformers
Safetensors
English
modernbert
log-analysis
severity-classification
aiops
observability
Eval Results (legacy)
text-embeddings-inference
Instructions to use hazemkhaled-94/modernlogbert-wce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hazemkhaled-94/modernlogbert-wce with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hazemkhaled-94/modernlogbert-wce")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hazemkhaled-94/modernlogbert-wce") model = AutoModelForSequenceClassification.from_pretrained("hazemkhaled-94/modernlogbert-wce", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 099690557f3692e9e9ec6960a98ddd0bdab6ed54cc3c0cccc2b82a9ce8a78c21
- Size of remote file:
- 5.33 kB
- SHA256:
- 5349228ae8092adfc9c0c14168a787e8cac0999986c542de4996bb0c9d284330
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