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--- |
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tags: autotrain |
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language: ja |
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widget: |
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- text: "RustでWebAssemblyインタプリタを作った話+webassembly+rust" |
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- text: "Goのロギングライブラリ 2021年冬 golang library logging go" |
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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" |
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datasets: |
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- vabadeh213/autotrain-data-iine_classification10 |
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co2_eq_emissions: 7.351885824089346 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Binary Classification |
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- Model ID: 737422470 |
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- CO2 Emissions (in grams): 7.351885824089346 |
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## Validation Metrics |
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- Loss: 0.39456263184547424 |
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- Accuracy: 0.8279088689991864 |
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- Precision: 0.6869806094182825 |
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- Recall: 0.17663817663817663 |
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- AUC: 0.7937892215111646 |
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- F1: 0.2810198300283286 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ 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 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("vabadeh213/autotrain-iine_classification10-737422470", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("vabadeh213/autotrain-iine_classification10-737422470", use_auth_token=True) |
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inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
