vabadeh213's picture
Update README.md
285f9e2
metadata
tags: autotrain
language: ja
widget:
  - text: RustでWebAssemblyインタプリタを作った話+webassembly+rust
  - text: Goのロギングライブラリ 2021年冬 golang library logging go
  - 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)