Instructions to use DevBeom/dbert_Beomsang with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DevBeom/dbert_Beomsang with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DevBeom/dbert_Beomsang")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DevBeom/dbert_Beomsang") model = AutoModelForSequenceClassification.from_pretrained("DevBeom/dbert_Beomsang") - Notebooks
- Google Colab
- Kaggle
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="DevBeom/dbert_Beomsang")# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("DevBeom/dbert_Beomsang")
model = AutoModelForSequenceClassification.from_pretrained("DevBeom/dbert_Beomsang")Quick Links
# Gated model: Login with a HF token with gated access permission hf auth login