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autotrain-mlsec-1013333734
deepesh0x/autotrain-mlsec-1013333734
autotrain-mlsec-1013333734 is a text classification model from deepesh0x. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 1013333734 - CO2 Emissions (in grams): 308.7012650779217
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Repo size
2.8 GB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Jun 21, 2022
- Updated
- Jun 21, 2022
- SHA
- 911b363d
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1013333734
- CO2 Emissions (in grams): 308.7012650779217
Validation Metrics
- Loss: 0.20877738296985626
- Accuracy: 0.9396153846153846
- Precision: 0.9291791791791791
- Recall: 0.9518072289156626
- AUC: 0.9671522989580735
- F1: 0.9403570976320121
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/deepesh0x/autotrain-mlsec-1013333734
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-mlsec-1013333734", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("deepesh0x/autotrain-mlsec-1013333734", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- en
- Created
- Jun 21, 2022
- Updated
- Jun 21, 2022