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country-recognition
Maxbnza/country-recognition
country-recognition is a text classification model from Maxbnza. 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: 1062136864 - CO2 Emissions (in grams): 141.11976199388627
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4.5 GB
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2
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jun 30, 2022
- Updated
- Jun 30, 2022
- SHA
- 246f60af
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1062136864
- CO2 Emissions (in grams): 141.11976199388627
Validation Metrics
- Loss: 0.10147109627723694
- Accuracy: 0.9859325979151907
- Macro F1: 0.9715036017680622
- Micro F1: 0.9859325979151907
- Weighted F1: 0.9859070541468058
- Macro Precision: 0.9732956651937184
- Micro Precision: 0.9859325979151907
- Weighted Precision: 0.9860574596777458
- Macro Recall: 0.970199341807239
- Micro Recall: 0.9859325979151907
- Weighted Recall: 0.9859325979151907
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/Maxbnza/autotrain-address-training-1062136864
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Maxbnza/autotrain-address-training-1062136864", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Maxbnza/autotrain-address-training-1062136864", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Languages
- unk
- Created
- Jun 30, 2022
- Updated
- Jun 30, 2022