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autotrain-finance_data_classification-2694580522
samaresh55/autotrain-finance_data_classification-2694580522
autotrain-finance_data_classification-2694580522 is a text classification model from samaresh55. 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: 2694580522 - CO2 Emissions (in grams): 4.2215
All-time downloads
495
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Repo size
877 MB
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1
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Repo makeup
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jan 3, 2023
- Updated
- Jan 6, 2023
- SHA
- 261f3cf6
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2694580522
- CO2 Emissions (in grams): 4.2215
Validation Metrics
- Loss: 0.227
- Accuracy: 0.950
- Macro F1: 0.931
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.956
- Micro Precision: 0.950
- Weighted Precision: 0.950
- Macro Recall: 0.914
- Micro Recall: 0.950
- Weighted Recall: 0.950
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/samaresh55/autotrain-finance_data_classification-2694580522
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("samaresh55/autotrain-finance_data_classification-2694580522", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("samaresh55/autotrain-finance_data_classification-2694580522", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt",truncation=True)
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- unk
- Created
- Jan 3, 2023
- Updated
- Jan 6, 2023