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---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- kSaluja/autonlp-data-tele_red_data_model
co2_eq_emissions: 2.379476355147211
---
# Model Trained Using AutoNLP
- Problem type: Entity Extraction
- Model ID: 585716433
- CO2 Emissions (in grams): 2.379476355147211
## Validation Metrics
- Loss: 0.15210922062397003
- Accuracy: 0.9724770642201835
- Precision: 0.950836820083682
- Recall: 0.9625838333921638
- F1: 0.9566742676723382
## 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 AutoNLP"}' https://api-inference.huggingface.co/models/kSaluja/autonlp-tele_red_data_model-585716433
```
Or Python API:
```
from transformers import AutoModelForTokenClassification, AutoTokenizer
model = AutoModelForTokenClassification.from_pretrained("kSaluja/autonlp-tele_red_data_model-585716433", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("kSaluja/autonlp-tele_red_data_model-585716433", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
``` |