README.md

metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - agnihotri/autotrain-data-contract_type
co2_eq_emissions: 0.07610944071640048

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 809725368
• CO2 Emissions (in grams): 0.07610944071640048

Validation Metrics

• Loss: 0.05312908813357353
• Accuracy: 0.9911504424778761
• Macro F1: 0.9912087912087912
• Micro F1: 0.9911504424778761
• Weighted F1: 0.9908586988233007
• Macro Precision: 0.9942857142857143
• Micro Precision: 0.9911504424778761
• Weighted Precision: 0.9924146649810366
• Macro Recall: 0.99
• Micro Recall: 0.9911504424778761
• Weighted Recall: 0.9911504424778761

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/agnihotri/autotrain-contract_type-809725368

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("agnihotri/autotrain-contract_type-809725368", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("agnihotri/autotrain-contract_type-809725368", use_auth_token=True)

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

outputs = model(**inputs)