Instructions to use Yah216/Arabic_poem_meter_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yah216/Arabic_poem_meter_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yah216/Arabic_poem_meter_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yah216/Arabic_poem_meter_classification") model = AutoModelForSequenceClassification.from_pretrained("Yah216/Arabic_poem_meter_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: ar | |
| widget: | |
| - text: "قفا نبك من ذِكرى حبيب ومنزلِ بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ" | |
| - text: "سَلو قَلبي غَداةَ سَلا وَثابا لَعَلَّ عَلى الجَمالِ لَهُ عِتابا" | |
| # Model Trained Using AutoTrain | |
| - Problem type: Multi-class Classification | |
| - Model ID: 913229914 | |
| - CO2 Emissions (in grams): 1.8892280988467902 | |
| ## Validation Metrics | |
| - Loss: 1.0592747926712036 | |
| - Accuracy: 0.6535535147098981 | |
| - Macro F1: 0.46508274468173677 | |
| - Micro F1: 0.6535535147098981 | |
| - Weighted F1: 0.6452975497424681 | |
| - Macro Precision: 0.6288501119526966 | |
| - Micro Precision: 0.6535535147098981 | |
| - Weighted Precision: 0.6818087199275457 | |
| - Macro Recall: 0.3910156950920188 | |
| - Micro Recall: 0.6535535147098981 | |
| - Weighted Recall: 0.6535535147098981 | |
| ## 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/Yah216/autotrain-poem_meter_classification-913229914 | |
| ``` | |
| Or Python API: | |
| ``` | |
| from transformers import AutoModelForSequenceClassification, AutoTokenizer | |
| model = AutoModelForSequenceClassification.from_pretrained("Yah216/autotrain-poem_meter_classification-913229914", use_auth_token=True) | |
| tokenizer = AutoTokenizer.from_pretrained("Yah216/autotrain-poem_meter_classification-913229914", use_auth_token=True) | |
| inputs = tokenizer("I love AutoTrain", return_tensors="pt") | |
| outputs = model(**inputs) | |
| ``` |