README.md

metadata

tags: autonlp
language: zh
widget:
  - text: I love AutoNLP 🤗
datasets:
  - kyleinincubated/autonlp-data-cat333
co2_eq_emissions: 2.267288583123193

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 624217911
• CO2 Emissions (in grams): 2.267288583123193

Validation Metrics

• Loss: 0.39670249819755554
• Accuracy: 0.9098901098901099
• Macro F1: 0.7398394202169645
• Micro F1: 0.9098901098901099
• Weighted F1: 0.9073329464119164
• Macro Precision: 0.7653753530396269
• Micro Precision: 0.9098901098901099
• Weighted Precision: 0.9096917983040914
• Macro Recall: 0.7382843728794468
• Micro Recall: 0.9098901098901099
• Weighted Recall: 0.9098901098901099

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/kyleinincubated/autonlp-cat333-624217911

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("kyleinincubated/autonlp-cat333-624217911", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("kyleinincubated/autonlp-cat333-624217911", use_auth_token=True)

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

outputs = model(**inputs)