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autotrain-Test_2-789524315
Rem59/autotrain-Test_2-789524315
autotrain-Test_2-789524315 is a text classification model from Rem59. 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: 789524315 - CO2 Emissions (in grams): 2.0134443204822188
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- Apr 26, 2022
- Updated
- Apr 26, 2022
- SHA
- 10cd8808
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 789524315
- CO2 Emissions (in grams): 2.0134443204822188
Validation Metrics
- Loss: 0.8042349815368652
- Accuracy: 0.6904761904761905
- Macro F1: 0.27230046948356806
- Micro F1: 0.6904761904761905
- Weighted F1: 0.5640509725016768
- Macro Precision: 0.23015873015873015
- Micro Precision: 0.6904761904761905
- Weighted Precision: 0.4767573696145125
- Macro Recall: 0.3333333333333333
- Micro Recall: 0.6904761904761905
- Weighted Recall: 0.6904761904761905
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/Rem59/autotrain-Test_2-789524315
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Rem59/autotrain-Test_2-789524315", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Rem59/autotrain-Test_2-789524315", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- Languages
- unk
- Created
- Apr 26, 2022
- Updated
- Apr 26, 2022