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autotrain-preesmetextclassifier-2437575785
acrowth/autotrain-preesmetextclassifier-2437575785
autotrain-preesmetextclassifier-2437575785 is a text classification model from acrowth. 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: 2437575785 - CO2 Emissions (in grams): 3.3212
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At a glance
- Task
- Text Classification
- Library
- transformers
- Access
- Public
- Created
- Dec 12, 2022
- Updated
- Dec 12, 2022
- SHA
- 07fd7690
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2437575785
- CO2 Emissions (in grams): 3.3212
Validation Metrics
- Loss: 0.142
- Accuracy: 0.970
- Macro F1: 0.572
- Micro F1: 0.970
- Weighted F1: 0.960
- Macro Precision: 0.592
- Micro Precision: 0.970
- Weighted Precision: 0.951
- Macro Recall: 0.556
- Micro Recall: 0.970
- Weighted Recall: 0.970
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/acrowth/autotrain-preesmetextclassifier-2437575785
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("acrowth/autotrain-preesmetextclassifier-2437575785", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("acrowth/autotrain-preesmetextclassifier-2437575785", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Languages
- fr
- Created
- Dec 12, 2022
- Updated
- Dec 12, 2022