sgugit-model-v3 / README.md
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Commit From AutoTrain
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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)