README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - giuseppemartino/autotrain-data-bert-base-xxl-uncased-ft
co2_eq_emissions:
  emissions: 0.8040280701527436

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 85992142947
• CO2 Emissions (in grams): 0.8040

Validation Metrics

• Loss: 0.399
• Accuracy: 0.832
• Precision: 0.810
• Recall: 0.761
• AUC: 0.900
• F1: 0.785

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/giuseppemartino/autotrain-bert-base-xxl-uncased-ft-85992142947

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("giuseppemartino/autotrain-bert-base-xxl-uncased-ft-85992142947", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("giuseppemartino/autotrain-bert-base-xxl-uncased-ft-85992142947", use_auth_token=True)

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

outputs = model(**inputs)