README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - lucianpopa/autonlp-data-TREC-classification
co2_eq_emissions: 15.186006626915715

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 522314623
• CO2 Emissions (in grams): 15.186006626915715

Validation Metrics

• Loss: 0.24612033367156982
• Accuracy: 0.9643183897529735
• Macro F1: 0.9493690949638435
• Micro F1: 0.9643183897529735
• Weighted F1: 0.9642384162837268
• Macro Precision: 0.9372705571897225
• Micro Precision: 0.9643183897529735
• Weighted Precision: 0.9652870438320825
• Macro Recall: 0.9649638583139503
• Micro Recall: 0.9643183897529735
• Weighted Recall: 0.9643183897529735

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 AutoNLP"}' https://api-inference.huggingface.co/models/lucianpopa/autonlp-TREC-classification-522314623

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("lucianpopa/autonlp-TREC-classification-522314623", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("lucianpopa/autonlp-TREC-classification-522314623", use_auth_token=True)

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

outputs = model(**inputs)