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autotrain-Napkin-872827783
Yarn007/autotrain-Napkin-872827783
autotrain-Napkin-872827783 is a text classification model from Yarn007. 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: 872827783 - CO2 Emissions (in grams): 0.020162211418903533
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 16, 2022
- Updated
- May 16, 2022
- SHA
- 75576b61
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 872827783
- CO2 Emissions (in grams): 0.020162211418903533
Validation Metrics
- Loss: 0.25198695063591003
- Accuracy: 0.9325714285714286
- Macro F1: 0.9254931094274171
- Micro F1: 0.9325714285714286
- Weighted F1: 0.9323540959391766
- Macro Precision: 0.9286720054236212
- Micro Precision: 0.9325714285714286
- Weighted Precision: 0.9324375609546055
- Macro Recall: 0.9227549386201338
- Micro Recall: 0.9325714285714286
- Weighted Recall: 0.9325714285714286
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/Yarn007/autotrain-Napkin-872827783
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Yarn007/autotrain-Napkin-872827783", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Yarn007/autotrain-Napkin-872827783", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- unk
- Created
- May 16, 2022
- Updated
- May 16, 2022