README.md

metadata

tags: autonlp
language: nl
widget:
  - text: I love AutoNLP 🤗
datasets:
  - maximedb/autonlp-data-vaccinchat
co2_eq_emissions: 14.525955245648218

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 22134694
• CO2 Emissions (in grams): 14.525955245648218

Validation Metrics

• Loss: 1.7039562463760376
• Accuracy: 0.6369376479873717
• Macro F1: 0.5363181342408181
• Micro F1: 0.6369376479873717
• Weighted F1: 0.6309793486221543
• Macro Precision: 0.5533353910494714
• Micro Precision: 0.6369376479873717
• Weighted Precision: 0.676981050732216
• Macro Recall: 0.5828723356986293
• Micro Recall: 0.6369376479873717
• Weighted Recall: 0.6369376479873717

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/maximedb/autonlp-vaccinchat-22134694

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("maximedb/autonlp-vaccinchat-22134694", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("maximedb/autonlp-vaccinchat-22134694", use_auth_token=True)

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

outputs = model(**inputs)