0 1
---
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)
```