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autotrain-iptc-classification-v2-41840107634
milyiyo/autotrain-iptc-classification-v2-41840107634
autotrain-iptc-classification-v2-41840107634 is a text classification model from milyiyo. 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: 41840107634 - CO2 Emissions (in grams): 0.7917
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Repo size
880 MB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 18, 2023
- Updated
- Mar 18, 2023
- SHA
- 3a1b8493
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 41840107634
- CO2 Emissions (in grams): 0.7917
Validation Metrics
- Loss: 1.345
- Accuracy: 0.732
- Macro F1: 0.514
- Micro F1: 0.732
- Weighted F1: 0.681
- Macro Precision: 0.513
- Micro Precision: 0.732
- Weighted Precision: 0.660
- Macro Recall: 0.542
- Micro Recall: 0.732
- Weighted Recall: 0.732
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/milyiyo/autotrain-iptc-classification-v2-41840107634
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("milyiyo/autotrain-iptc-classification-v2-41840107634", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("milyiyo/autotrain-iptc-classification-v2-41840107634", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- es
- Created
- Mar 18, 2023
- Updated
- Mar 18, 2023