| --- |
| tags: |
| - autotrain |
| - text-classification |
| language: |
| - en |
| widget: |
| - text: "I love AutoTrain 🤗" |
| datasets: |
| - badalsahani/autotrain-data-pdf-classification |
| co2_eq_emissions: |
| emissions: 6.061459826922492 |
| --- |
| |
| # Model Trained Using AutoTrain |
|
|
| - Problem type: Multi-class Classification |
| - Model ID: 3447993987 |
| - CO2 Emissions (in grams): 6.0615 |
|
|
| ## Validation Metrics |
|
|
| - Loss: 0.005 |
| - Accuracy: 1.000 |
| - Macro F1: 1.000 |
| - Micro F1: 1.000 |
| - Weighted F1: 1.000 |
| - Macro Precision: 1.000 |
| - Micro Precision: 1.000 |
| - Weighted Precision: 1.000 |
| - Macro Recall: 1.000 |
| - Micro Recall: 1.000 |
| - Weighted Recall: 1.000 |
|
|
|
|
| ## 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/badalsahani/autotrain-pdf-classification-3447993987 |
| ``` |
|
|
| Or Python API: |
|
|
| ``` |
| from transformers import AutoModelForSequenceClassification, AutoTokenizer |
| |
| model = AutoModelForSequenceClassification.from_pretrained("badalsahani/autotrain-pdf-classification-3447993987", use_auth_token=True) |
| |
| tokenizer = AutoTokenizer.from_pretrained("badalsahani/autotrain-pdf-classification-3447993987", use_auth_token=True) |
| |
| inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
| |
| outputs = model(**inputs) |
| ``` |
