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emo_nojoylove
crcb/emo_nojoylove
emo_nojoylove is a text classification model from crcb. 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: 751422966 - CO2 Emissions (in grams): 12.236769332727217
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 17, 2022
- Updated
- Apr 17, 2022
- SHA
- f83f7c99
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 751422966
- CO2 Emissions (in grams): 12.236769332727217
Validation Metrics
- Loss: 0.1358409821987152
- Accuracy: 0.9397905759162304
- Macro F1: 0.9096049124431982
- Micro F1: 0.9397905759162304
- Weighted F1: 0.9395954853807672
- Macro Precision: 0.919807346649452
- Micro Precision: 0.9397905759162304
- Weighted Precision: 0.9407259082357824
- Macro Recall: 0.9024000547645126
- Micro Recall: 0.9397905759162304
- Weighted Recall: 0.9397905759162304
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/crcb/autotrain-emo_carer_nojoylove-751422966
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422966", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422966", 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
- Apr 17, 2022
- Updated
- Apr 17, 2022