README.md

metadata

tags:
  - autotrain
  - token-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - teacookies/autotrain-data-17101457-1200cut_rich_neg
co2_eq_emissions:
  emissions: 15.90515729014607

Model Trained Using AutoTrain

• Problem type: Entity Extraction
• Model ID: 1782461850
• CO2 Emissions (in grams): 15.9052

Validation Metrics

• Loss: 0.022
• Accuracy: 0.994
• Precision: 0.736
• Recall: 0.804
• F1: 0.769

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 AutoTrain"}' https://api-inference.huggingface.co/models/teacookies/autotrain-17101457-1200cut_rich_neg-1782461850

Or Python API:

from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("teacookies/autotrain-17101457-1200cut_rich_neg-1782461850", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("teacookies/autotrain-17101457-1200cut_rich_neg-1782461850", use_auth_token=True)

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

outputs = model(**inputs)