README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - davis901/autotrain-data-imdb-textclassification
co2_eq_emissions:
  emissions: 2.683579313085358

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 46471115127
• CO2 Emissions (in grams): 2.6836

Validation Metrics

• Loss: 0.000
• Accuracy: 1.000
• Precision: 1.000
• Recall: 1.000
• AUC: 1.000
• F1: 1.000

Usage

You can use cURL to access this model:

$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/davis901/autotrain-imdb-textclassification-46471115127

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("davis901/autotrain-imdb-textclassification-46471115127", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("davis901/autotrain-imdb-textclassification-46471115127", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)