Text Classification
Transformers
Safetensors
English
distilbert
devops
sre
incident-triage
mlops
fastapi
python
text-embeddings-inference
Instructions to use dongkoony/devops-incident-triage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dongkoony/devops-incident-triage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dongkoony/devops-incident-triage")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dongkoony/devops-incident-triage") model = AutoModelForSequenceClassification.from_pretrained("dongkoony/devops-incident-triage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dongkoony/devops-incident-triage: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/dongkoony/devops-incident-triage/resolve/main/tokenizer.json
- Command line
-
hf download hf://dongkoony/devops-incident-triage/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/dongkoony/devops-incident-triage/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.