Instructions to use interneuronai/asiancuisinefooddelivery_onlineorderclassification_bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use interneuronai/asiancuisinefooddelivery_onlineorderclassification_bart with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="interneuronai/asiancuisinefooddelivery_onlineorderclassification_bart")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("interneuronai/asiancuisinefooddelivery_onlineorderclassification_bart") model = AutoModelForSequenceClassification.from_pretrained("interneuronai/asiancuisinefooddelivery_onlineorderclassification_bart") - Notebooks
- Google Colab
- Kaggle
AsianCuisineFoodDelivery_OnlineOrderClassification
Description: Categorize online orders based on dish types, ingredients, or cooking methods to optimize food preparation processes, inventory management, and delivery logistics.
How to Use
Here is how to use this model to classify text into different categories:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_name = "interneuronai/asiancuisinefooddelivery_onlineorderclassification_bart"
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
def classify_text(text):
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)
outputs = model(**inputs)
predictions = outputs.logits.argmax(-1)
return predictions.item()
text = "Your text here"
print("Category:", classify_text(text))
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