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---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- doctorlan/autonlp-data-JD-bert
co2_eq_emissions: 5.919372931976555
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 653619233
- CO2 Emissions (in grams): 5.919372931976555
## Validation Metrics
- Loss: 0.15083155035972595
- Accuracy: 0.952650883627876
- Precision: 0.9631399317406143
- Recall: 0.9412941961307538
- AUC: 0.9828776962419389
- F1: 0.9520917678812415
## 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/doctorlan/autonlp-JD-bert-653619233
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("doctorlan/autonlp-JD-bert-653619233", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("doctorlan/autonlp-JD-bert-653619233", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
``` |