README.md

metadata

tags:
  - autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - nihaldsouza1/autonlp-data-yelp-rating-classification
co2_eq_emissions: 15.62335109262394

Custom-trained user model

• Problem type: Multi-class Classification
• Model ID: 545015430
• CO2 Emissions (in grams): 15.62335109262394

Validation Metrics

• Loss: 0.7870086431503296
• Accuracy: 0.6631428571428571
• Macro F1: 0.6613073053700258
• Micro F1: 0.6631428571428571
• Weighted F1: 0.661157273964887
• Macro Precision: 0.6626911151999393
• Micro Precision: 0.6631428571428571
• Weighted Precision: 0.662191421927851
• Macro Recall: 0.6629735627465572
• Micro Recall: 0.6631428571428571
• Weighted Recall: 0.6631428571428571

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/nihaldsouza1/autonlp-yelp-rating-classification-545015430

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("nihaldsouza1/autonlp-yelp-rating-classification-545015430", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("nihaldsouza1/autonlp-yelp-rating-classification-545015430", use_auth_token=True)

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

outputs = model(**inputs)