README.md

metadata

tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - doctorlan/autonlp-data-ctrip
co2_eq_emissions: 24.879856894708393

Model Trained Using AutoNLP

• Problem type: Binary Classification
• Model ID: 653519223
• CO2 Emissions (in grams): 24.879856894708393

Validation Metrics

• Loss: 0.14671853184700012
• Accuracy: 0.9676666666666667
• Precision: 0.9794159885112494
• Recall: 0.9742857142857143
• AUC: 0.9901396825396825
• F1: 0.9768441155407017

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 AutoNLP"}' https://api-inference.huggingface.co/models/doctorlan/autonlp-ctrip-653519223

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("doctorlan/autonlp-ctrip-653519223", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("doctorlan/autonlp-ctrip-653519223", use_auth_token=True)

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

outputs = model(**inputs)