README.md

metadata

tags: autonlp
language: zh
widget:
  - text: I love AutoNLP 🤗
datasets:
  - ysslang/autonlp-data-test
co2_eq_emissions: 10.9230691350863

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 459011902
• CO2 Emissions (in grams): 10.9230691350863

Validation Metrics

• Loss: 0.7189690470695496
• Accuracy: 0.7453263867606497
• Macro F1: 0.630810193227066
• Micro F1: 0.7453263867606497
• Weighted F1: 0.7399327942874923
• Macro Precision: 0.656237447101913
• Micro Precision: 0.7453263867606497
• Weighted Precision: 0.7410161412822164
• Macro Recall: 0.6340140718425453
• Micro Recall: 0.7453263867606497
• Weighted Recall: 0.7453263867606497

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/ysslang/autonlp-test-459011902

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("ysslang/autonlp-test-459011902", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("ysslang/autonlp-test-459011902", use_auth_token=True)

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

outputs = model(**inputs)