README.md

metadata

tags:
  - autotrain
  - text-classification
  - bert
  - patent-deberta
  - patent-classification
language:
  - en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - eeshan/autotrain-data-r-nr-categorization
co2_eq_emissions:
  emissions: 17.1013640357776
license: apache-2.0
metrics:
  - accuracy
pipeline_tag: text-classification

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 3075087647
• CO2 Emissions (in grams): 17.1014

Validation Metrics

• Loss: 0.000
• Accuracy: 1.000
• Precision: 1.000
• Recall: 1.000
• AUC: 1.000
• F1: 1.000

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/eeshan/autotrain-r-nr-categorization-3075087647

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("eeshan/autotrain-r-nr-categorization-3075087647", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("eeshan/autotrain-r-nr-categorization-3075087647", use_auth_token=True)

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

outputs = model(**inputs)