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autotrain-sentiment_analysis-39304102733
raghuram13/autotrain-sentiment_analysis-39304102733
autotrain-sentiment_analysis-39304102733 is a text classification model from raghuram13. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 39304102733 - CO2 Emissions (in grams): 1.3917
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Repo size
1.1 GB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- deberta
- Access
- Public
- Created
- Mar 6, 2023
- Updated
- Mar 6, 2023
- SHA
- 849816ec
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 39304102733
- CO2 Emissions (in grams): 1.3917
Validation Metrics
- Loss: 0.200
- Accuracy: 0.937
- Precision: 0.936
- Recall: 0.940
- AUC: 0.982
- F1: 0.938
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/raghuram13/autotrain-sentiment_analysis-39304102733
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("raghuram13/autotrain-sentiment_analysis-39304102733", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("raghuram13/autotrain-sentiment_analysis-39304102733", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- deberta
- Languages
- en
- Created
- Mar 6, 2023
- Updated
- Mar 6, 2023