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autotrain-kaggle-effective-arguments-1086739296
Danitg95/autotrain-kaggle-effective-arguments-1086739296
autotrain-kaggle-effective-arguments-1086739296 is a text classification model from Danitg95. 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: 1086739296 - CO2 Emissions (in grams): 5.2497206864306065
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Jul 4, 2022
- Updated
- Jul 4, 2022
- SHA
- 5ad53906
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1086739296
- CO2 Emissions (in grams): 5.2497206864306065
Validation Metrics
- Loss: 0.744236171245575
- Accuracy: 0.6719238613188308
- Macro F1: 0.5450301061253738
- Micro F1: 0.6719238613188308
- Weighted F1: 0.6349879540623229
- Macro Precision: 0.6691326843926052
- Micro Precision: 0.6719238613188308
- Weighted Precision: 0.6706209016443158
- Macro Recall: 0.5426627824078865
- Micro Recall: 0.6719238613188308
- Weighted Recall: 0.6719238613188308
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/Danitg95/autotrain-kaggle-effective-arguments-1086739296
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Danitg95/autotrain-kaggle-effective-arguments-1086739296", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Danitg95/autotrain-kaggle-effective-arguments-1086739296", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Jul 4, 2022
- Updated
- Jul 4, 2022