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autotrain-argument-feedback-1154042511
snap/autotrain-argument-feedback-1154042511
autotrain-argument-feedback-1154042511 is a text classification model from snap. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 1154042511 - CO2 Emissions (in grams): 50.942111222257715
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jul 19, 2022
- Updated
- Jul 19, 2022
- SHA
- a6d87bab
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1154042511
- CO2 Emissions (in grams): 50.942111222257715
Validation Metrics
- Loss: 0.7391096353530884
- Accuracy: 0.672331747110809
- Macro F1: 0.5302988889038903
- Micro F1: 0.672331747110809
- Weighted F1: 0.628333699928783
- Macro Precision: 0.6916740835116003
- Micro Precision: 0.672331747110809
- Weighted Precision: 0.6810625595246631
- Macro Recall: 0.5264405918447705
- Micro Recall: 0.672331747110809
- Weighted Recall: 0.672331747110809
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/snap/autotrain-argument-feedback-1154042511
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("snap/autotrain-argument-feedback-1154042511", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("snap/autotrain-argument-feedback-1154042511", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Jul 19, 2022
- Updated
- Jul 19, 2022