Robertabase_Ana4 / README.md
abhishek's picture
abhishek HF staff
Commit From AutoNLP
5d7d0e2
metadata
tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - vinaydngowda/autonlp-data-case-classify-xlnet
co2_eq_emissions: 19.964760910364927

Model Trained Using AutoNLP

  • Problem type: Multi-class Classification
  • Model ID: 496213536
  • CO2 Emissions (in grams): 19.964760910364927

Validation Metrics

  • Loss: 0.7149562835693359
  • Accuracy: 0.8092592592592592
  • Macro F1: 0.8085189591849891
  • Micro F1: 0.8092592592592593
  • Weighted F1: 0.8085189591849888
  • Macro Precision: 0.8137745564384112
  • Micro Precision: 0.8092592592592592
  • Weighted Precision: 0.8137745564384112
  • Macro Recall: 0.8092592592592592
  • Micro Recall: 0.8092592592592592
  • Weighted Recall: 0.8092592592592592

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/vinaydngowda/autonlp-case-classify-xlnet-496213536

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("vinaydngowda/autonlp-case-classify-xlnet-496213536", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("vinaydngowda/autonlp-case-classify-xlnet-496213536", use_auth_token=True)

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

outputs = model(**inputs)