README.md

metadata

tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - alvp/autonlp-data-alberti-stanza-names
co2_eq_emissions: 8.612473981829835

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 34318169
• CO2 Emissions (in grams): 8.612473981829835

Validation Metrics

• Loss: 1.3520570993423462
• Accuracy: 0.6083916083916084
• Macro F1: 0.5420169617715481
• Micro F1: 0.6083916083916084
• Weighted F1: 0.5963328136975058
• Macro Precision: 0.5864033493660455
• Micro Precision: 0.6083916083916084
• Weighted Precision: 0.6364793882921277
• Macro Recall: 0.5545405576555766
• Micro Recall: 0.6083916083916084
• Weighted Recall: 0.6083916083916084

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/alvp/autonlp-alberti-stanza-names-34318169

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("alvp/autonlp-alberti-stanza-names-34318169", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("alvp/autonlp-alberti-stanza-names-34318169", use_auth_token=True)

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

outputs = model(**inputs)