README.md

metadata

tags: autotrain
language: ja
widget:
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  - text: VimとTUIツールをなめらかに切り替える ranger tig git vim
datasets:
  - vabadeh213/autotrain-data-iine_classification10
co2_eq_emissions: 7.351885824089346

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 737422470
• CO2 Emissions (in grams): 7.351885824089346

Validation Metrics

• Loss: 0.39456263184547424
• Accuracy: 0.8279088689991864
• Precision: 0.6869806094182825
• Recall: 0.17663817663817663
• AUC: 0.7937892215111646
• F1: 0.2810198300283286

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/vabadeh213/autotrain-iine_classification10-737422470

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("vabadeh213/autotrain-iine_classification10-737422470", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("vabadeh213/autotrain-iine_classification10-737422470", use_auth_token=True)

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

outputs = model(**inputs)