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autotrain-car-review-project-966432121
qualitydatalab/autotrain-car-review-project-966432121
autotrain-car-review-project-966432121 is a text classification model from qualitydatalab. 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: 966432121 - CO2 Emissions (in grams): 0.21529888368377176
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Jun 9, 2022
- Updated
- Jun 9, 2022
- SHA
- f28298b0
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 966432121
- CO2 Emissions (in grams): 0.21529888368377176
Validation Metrics
- Loss: 0.6013365983963013
- Accuracy: 0.737791286727457
- Macro F1: 0.729171012281939
- Micro F1: 0.737791286727457
- Weighted F1: 0.729171012281939
- Macro Precision: 0.7313770127538427
- Micro Precision: 0.737791286727457
- Weighted Precision: 0.7313770127538428
- Macro Recall: 0.737791286727457
- Micro Recall: 0.737791286727457
- Weighted Recall: 0.737791286727457
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 driving this car"}' https://api-inference.huggingface.co/models/qualitydatalab/autotrain-car-review-project-966432121
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("qualitydatalab/autotrain-car-review-project-966432121", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("qualitydatalab/autotrain-car-review-project-966432121", 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 9, 2022
- Updated
- Jun 9, 2022