Text Classification
Transformers
Safetensors
English
modernbert
food
drink
food-classification
caption-classification
knowledge-distillation
ettin
Eval Results (legacy)
text-embeddings-inference
Instructions to use mrdbourke/ettin-150m-food-or-drink-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrdbourke/ettin-150m-food-or-drink-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrdbourke/ettin-150m-food-or-drink-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrdbourke/ettin-150m-food-or-drink-classifier") model = AutoModelForSequenceClassification.from_pretrained("mrdbourke/ettin-150m-food-or-drink-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K