README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - SH-W/autotrain-data-5000_koi
co2_eq_emissions:
  emissions: 3.920765439350259

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 77927140735
• CO2 Emissions (in grams): 3.9208

Validation Metrics

• Loss: 2.432
• Accuracy: 0.415
• Macro F1: 0.410
• Micro F1: 0.415
• Weighted F1: 0.410
• Macro Precision: 0.459
• Micro Precision: 0.415
• Weighted Precision: 0.456
• Macro Recall: 0.413
• Micro Recall: 0.415
• Weighted Recall: 0.415

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/SH-W/autotrain-5000_koi-77927140735

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("SH-W/autotrain-5000_koi-77927140735", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("SH-W/autotrain-5000_koi-77927140735", use_auth_token=True)

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

outputs = model(**inputs)