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climate_sentiment_classifier
Sachinkelenjaguri/climate_sentiment_classifier
climate_sentiment_classifier is a text classification model from Sachinkelenjaguri. Use it when you need a label for a piece of text. It is set up for transformers.
0- Risk <br 1-Neutral <br 2-Oppertunity <br
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Repo size
536 MB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- May 3, 2023
- Updated
- May 3, 2023
- SHA
- a2673e98
Try a prompt
Model card
From the Hugging Face model README
Class:
0- Risk <br> 1-Neutral <br> 2-Oppertunity <br>
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 55107128708
- CO2 Emissions (in grams): 0.0012
Validation Metrics
- Loss: 0.516
- Accuracy: 0.806
- Macro F1: 0.783
- Micro F1: 0.806
- Weighted F1: 0.806
- Macro Precision: 0.777
- Micro Precision: 0.806
- Weighted Precision: 0.809
- Macro Recall: 0.793
- Micro Recall: 0.806
- Weighted Recall: 0.806
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/Sachinkelenjaguri/Sachinkelenjaguri/climate_sentiment_classifier
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Sachinkelenjaguri/climate_sentiment_classifier", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Sachinkelenjaguri/climate_sentiment_classifier", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- unk
- Created
- May 3, 2023
- Updated
- May 3, 2023