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autotrain-mbtiNlp-798824628
Sathira/autotrain-mbtiNlp-798824628
autotrain-mbtiNlp-798824628 is a text classification model from Sathira. 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: 798824628 - CO2 Emissions (in grams): 121.67185089502216
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Repo size
536 MB
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3
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Apr 28, 2022
- Updated
- Apr 28, 2022
- SHA
- 5cec12d4
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 798824628
- CO2 Emissions (in grams): 121.67185089502216
Validation Metrics
- Loss: 0.5046824812889099
- Accuracy: 0.8472124039775673
- Macro F1: 0.7812978033330673
- Micro F1: 0.8472124039775673
- Weighted F1: 0.8464983956259307
- Macro Precision: 0.812208631055716
- Micro Precision: 0.8472124039775673
- Weighted Precision: 0.8478968364150775
- Macro Recall: 0.7593223884993787
- Micro Recall: 0.8472124039775673
- Weighted Recall: 0.8472124039775673
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/Sathira/autotrain-mbtiNlp-798824628
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Sathira/autotrain-mbtiNlp-798824628", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Sathira/autotrain-mbtiNlp-798824628", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Apr 28, 2022
- Updated
- Apr 28, 2022