README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - FEIMENG/autotrain-data-names-10k-en-cn-in-kr-jp-vn
co2_eq_emissions:
  emissions: 2.3523995441070964

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 42832109361
• CO2 Emissions (in grams): 2.3524

Validation Metrics

• Loss: 0.207
• Accuracy: 0.951
• Macro F1: 0.898
• Micro F1: 0.951
• Weighted F1: 0.950
• Macro Precision: 0.954
• Micro Precision: 0.951
• Weighted Precision: 0.952
• Macro Recall: 0.869
• Micro Recall: 0.951
• Weighted Recall: 0.951

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/FEIMENG/autotrain-names-10k-en-cn-in-kr-jp-vn-42832109361

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("FEIMENG/autotrain-names-10k-en-cn-in-kr-jp-vn-42832109361", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("FEIMENG/autotrain-names-10k-en-cn-in-kr-jp-vn-42832109361", use_auth_token=True)

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

outputs = model(**inputs)