README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: Shankesh designed this model from scratch 🤗
datasets:
  - sabhashanki/autotrain-data-khul-classify
co2_eq_emissions:
  emissions: 2.8092927891228863
inference: true

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 2396974951
• CO2 Emissions (in grams): 2.8093

Validation Metrics

• Loss: 0.635
• Accuracy: 0.840
• Macro F1: 0.834
• Micro F1: 0.840
• Weighted F1: 0.837
• Macro Precision: 0.839
• Micro Precision: 0.840
• Weighted Precision: 0.840
• Macro Recall: 0.836
• Micro Recall: 0.840
• Weighted Recall: 0.840

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/sabhashanki/autotrain-topic-prediction-latest-2396974951

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("sabhashanki/autotrain-topic-prediction-latest-2396974951", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("sabhashanki/autotrain-topic-prediction-latest-2396974951", use_auth_token=True)

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

outputs = model(**inputs)