README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - sasha/autotrain-data-BERTBase-imdb
co2_eq_emissions:
  emissions: 57.547246549422866

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 1275748794
• CO2 Emissions (in grams): 57.5472

Validation Metrics

• Loss: 0.174
• Accuracy: 0.936
• Precision: 0.924
• Recall: 0.949
• AUC: 0.982
• F1: 0.936

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-BERTBase-imdb-1275748794

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("sasha/autotrain-BERTBase-imdb-1275748794", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("sasha/autotrain-BERTBase-imdb-1275748794", use_auth_token=True)

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

outputs = model(**inputs)