README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - sasha/autotrain-data-DistilBERT-imdb
co2_eq_emissions:
  emissions: 0.0719533080486796

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 1275448783
• CO2 Emissions (in grams): 0.0720

Validation Metrics

• Loss: 0.224
• Accuracy: 0.912
• Precision: 0.896
• Recall: 0.931
• AUC: 0.972
• F1: 0.913

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/sasha/autotrain-DistilBERT-imdb-1275448783

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("sasha/autotrain-DistilBERT-imdb-1275448783", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("sasha/autotrain-DistilBERT-imdb-1275448783", use_auth_token=True)

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

outputs = model(**inputs)