README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
  - text: >-
      Bob accepts the challenge, and the next week they're standing in Saint
      Peters square. 'This isnt gonna work, he's never going to see me here when
      theres this much people. You stay here, I'll go talk to him and you'll see
      me on the balcony, the guards know me too.' Half an hour later, Bob and
      the pope appear side by side on the balcony. Bobs boss gets a heart
      attack, and Bob goes to visit him in the hospital. 
datasets:
  - akilesh96/autonlp-data-mrcooper_text_classification
co2_eq_emissions: 5.999771405025692

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 529614927
• CO2 Emissions (in grams): 5.999771405025692

Validation Metrics

• Loss: 0.7582379579544067
• Accuracy: 0.7636103151862464
• Macro F1: 0.770630619486531
• Micro F1: 0.7636103151862464
• Weighted F1: 0.765233270165301
• Macro Precision: 0.7746285216467107
• Micro Precision: 0.7636103151862464
• Weighted Precision: 0.7683270753840836
• Macro Recall: 0.7680576576961138
• Micro Recall: 0.7636103151862464
• Weighted Recall: 0.7636103151862464

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/akilesh96/autonlp-mrcooper_text_classification-529614927

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("akilesh96/autonlp-mrcooper_text_classification-529614927", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("akilesh96/autonlp-mrcooper_text_classification-529614927", use_auth_token=True)

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

outputs = model(**inputs)