Instructions to use Aktsvigun/deberta_cola_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/deberta_cola_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Aktsvigun/deberta_cola_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/deberta_cola_2") model = AutoModelForSequenceClassification.from_pretrained("Aktsvigun/deberta_cola_2") - Notebooks
- Google Colab
- Kaggle
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Aktsvigun/deberta_cola_2")# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/deberta_cola_2")
model = AutoModelForSequenceClassification.from_pretrained("Aktsvigun/deberta_cola_2")Quick Links
# Gated model: Login with a HF token with gated access permission hf auth login