README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - GRPUI/autotrain-data-sgugit-model-v3
co2_eq_emissions:
  emissions: 0.7899863264115066

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 91416144506
• CO2 Emissions (in grams): 0.7900

Validation Metrics

• Loss: 0.020
• Accuracy: 1.000
• Macro F1: 1.000
• Micro F1: 1.000
• Weighted F1: 1.000
• Macro Precision: 1.000
• Micro Precision: 1.000
• Weighted Precision: 1.000
• Macro Recall: 1.000
• Micro Recall: 1.000
• Weighted Recall: 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/GRPUI/autotrain-sgugit-model-v3-91416144506

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("GRPUI/autotrain-sgugit-model-v3-91416144506", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("GRPUI/autotrain-sgugit-model-v3-91416144506", use_auth_token=True)

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

outputs = model(**inputs)