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autotrain-emotion-detection-1366352626
rahulmallah/autotrain-emotion-detection-1366352626
autotrain-emotion-detection-1366352626 is a text classification model from rahulmallah. 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: 1366352626 - CO2 Emissions (in grams): 0.0372
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Repo size
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Sep 6, 2022
- Updated
- Sep 6, 2022
- SHA
- b13127f2
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1366352626
- CO2 Emissions (in grams): 0.0372
Validation Metrics
- Loss: 1.772
- Accuracy: 0.394
- Macro F1: 0.197
- Micro F1: 0.394
- Weighted F1: 0.351
- Macro Precision: 0.217
- Micro Precision: 0.394
- Weighted Precision: 0.345
- Macro Recall: 0.213
- Micro Recall: 0.394
- Weighted Recall: 0.394
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/rahulmallah/autotrain-emotion-detection-1366352626
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("rahulmallah/autotrain-emotion-detection-1366352626", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("rahulmallah/autotrain-emotion-detection-1366352626", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Sep 6, 2022
- Updated
- Sep 6, 2022