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autotrain-finance-consumer-complaints-issue-classification-2380974646
ChrisPCz/autotrain-finance-consumer-complaints-issue-classification-2380974646
autotrain-finance-consumer-complaints-issue-classification-2380974646 is a text classification model from ChrisPCz. 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: 2380974646 - CO2 Emissions (in grams): 89.4520
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Repo size
877 MB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Access
- Public
- Created
- Dec 8, 2022
- Updated
- Dec 8, 2022
- SHA
- 7e631c34
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2380974646
- CO2 Emissions (in grams): 89.4520
Validation Metrics
- Loss: 0.606
- Accuracy: 0.782
- Macro F1: 0.780
- Micro F1: 0.782
- Weighted F1: 0.780
- Macro Precision: 0.780
- Micro Precision: 0.782
- Weighted Precision: 0.780
- Macro Recall: 0.782
- Micro Recall: 0.782
- Weighted Recall: 0.782
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/ChrisPCz/autotrain-finance-consumer-complaints-issue-classification-2380974646
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("ChrisPCz/autotrain-finance-consumer-complaints-issue-classification-2380974646", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("ChrisPCz/autotrain-finance-consumer-complaints-issue-classification-2380974646", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Languages
- en
- Created
- Dec 8, 2022
- Updated
- Dec 8, 2022