File size: 1,342 Bytes
c212128 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
---
tags:
- autotrain
- text-classification
language:
- ar
widget:
- text: "I love AutoTrain"
datasets:
- DuhAlbared/autotrain-data-dru-textclassification
co2_eq_emissions:
emissions: 1.2953982175499286
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 66230136430
- CO2 Emissions (in grams): 1.2954
## Validation Metrics
- Loss: 0.296
- Accuracy: 0.916
- Macro F1: 0.916
- Micro F1: 0.916
- Weighted F1: 0.916
- Macro Precision: 0.917
- Micro Precision: 0.916
- Weighted Precision: 0.917
- Macro Recall: 0.916
- Micro Recall: 0.916
- Weighted Recall: 0.916
## 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/DuhAlbared/autotrain-dru-textclassification-66230136430
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("DuhAlbared/autotrain-dru-textclassification-66230136430", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("DuhAlbared/autotrain-dru-textclassification-66230136430", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
``` |