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autotrain-test-frank-896929583
vreese2414/autotrain-test-frank-896929583
autotrain-test-frank-896929583 is a text classification model from vreese2414. 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: 896929583 - CO2 Emissions (in grams): 20.85550802376653
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 24, 2022
- Updated
- May 24, 2022
- SHA
- 361ddd30
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 896929583
- CO2 Emissions (in grams): 20.85550802376653
Validation Metrics
- Loss: 0.8998094797134399
- Accuracy: 0.717983651226158
- Macro F1: 0.6850466044284794
- Micro F1: 0.717983651226158
- Weighted F1: 0.7093970537930665
- Macro Precision: 0.692166692035814
- Micro Precision: 0.717983651226158
- Weighted Precision: 0.7181745683190863
- Macro Recall: 0.6985625924834511
- Micro Recall: 0.717983651226158
- Weighted Recall: 0.717983651226158
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/vreese2414/autotrain-test-frank-896929583
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("vreese2414/autotrain-test-frank-896929583", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("vreese2414/autotrain-test-frank-896929583", 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
- May 24, 2022
- Updated
- May 24, 2022