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autotrain-emotion-detection-1587956110
hoshingakag/autotrain-emotion-detection-1587956110
autotrain-emotion-detection-1587956110 is a text classification model from hoshingakag. 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: 1587956110 - CO2 Emissions (in grams): 2.3491
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At a glance
- Task
- Text Classification
- Library
- transformers
- Access
- Public
- Created
- Sep 28, 2022
- Updated
- Sep 28, 2022
- SHA
- 0273743c
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1587956110
- CO2 Emissions (in grams): 2.3491
Validation Metrics
- Loss: 0.448
- Accuracy: 0.888
- Macro F1: 0.823
- Micro F1: 0.888
- Weighted F1: 0.884
- Macro Precision: 0.885
- Micro Precision: 0.888
- Weighted Precision: 0.890
- Macro Recall: 0.800
- Micro Recall: 0.888
- Weighted Recall: 0.888
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/hoshingakag/autotrain-emotion-detection-1587956110
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("hoshingakag/autotrain-emotion-detection-1587956110", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("hoshingakag/autotrain-emotion-detection-1587956110", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Languages
- en
- Created
- Sep 28, 2022
- Updated
- Sep 28, 2022