README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - yeye776/autotrain-data-intent-classification-6categories-roberta
co2_eq_emissions:
  emissions: 0.8352232431967963

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 89129143858
• CO2 Emissions (in grams): 0.8352

Validation Metrics

• Loss: 0.367
• Accuracy: 0.952
• Macro F1: 0.935
• Micro F1: 0.952
• Weighted F1: 0.951
• Macro Precision: 0.952
• Micro Precision: 0.952
• Weighted Precision: 0.955
• Macro Recall: 0.925
• Micro Recall: 0.952
• Weighted Recall: 0.952

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/yeye776/autotrain-intent-classification-6categories-roberta-89129143858

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("yeye776/autotrain-intent-classification-6categories-roberta-89129143858", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("yeye776/autotrain-intent-classification-6categories-roberta-89129143858", use_auth_token=True)

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

outputs = model(**inputs)