Text Classification
Safetensors
Transformers
English
LogClassifier
bert
log-classification
log feature
log-similarity
AIOps
Instructions to use rahulm-selector/log-classifier-BERT-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rahulm-selector/log-classifier-BERT-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rahulm-selector/log-classifier-BERT-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rahulm-selector/log-classifier-BERT-v1") model = AutoModelForSequenceClassification.from_pretrained("rahulm-selector/log-classifier-BERT-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f8c47e56234acf62221f6dbff89ea1c7781ceacdc875fe3bc92172c5b12c59b
- Size of remote file:
- 438 MB
- SHA256:
- 4ba495c2b569aab211af01eb8f4d972933d2aedfb3b6a4d0ee1bf3d81fe3d065
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.