README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - EduardoCam/autotrain-data-brisnko
co2_eq_emissions:
  emissions: 0.4115384416022771

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 97847147059
• CO2 Emissions (in grams): 0.4115

Validation Metrics

• Loss: 0.580
• Accuracy: 0.811
• Macro F1: 0.810
• Micro F1: 0.811
• Weighted F1: 0.814
• Macro Precision: 0.856
• Micro Precision: 0.811
• Weighted Precision: 0.847
• Macro Recall: 0.817
• Micro Recall: 0.811
• Weighted Recall: 0.811

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/EduardoCam/autotrain-brisnko-97847147059

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("EduardoCam/autotrain-brisnko-97847147059", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("EduardoCam/autotrain-brisnko-97847147059", use_auth_token=True)

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

outputs = model(**inputs)