|
--- |
|
tags: autotrain |
|
language: en |
|
widget: |
|
- text: "I love AutoTrain 🤗" |
|
datasets: |
|
- deepesh0x/autotrain-data-mlsec |
|
co2_eq_emissions: 33.183779535405364 |
|
--- |
|
|
|
# Model Trained Using AutoTrain |
|
|
|
- Problem type: Binary Classification |
|
- Model ID: 1013333726 |
|
- CO2 Emissions (in grams): 33.183779535405364 |
|
|
|
## Validation Metrics |
|
|
|
- Loss: 0.1998898833990097 |
|
- Accuracy: 0.9226923076923077 |
|
- Precision: 0.9269808389435525 |
|
- Recall: 0.9177134068187645 |
|
- AUC: 0.9785380985232148 |
|
- F1: 0.9223238438747907 |
|
|
|
## 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/deepesh0x/autotrain-mlsec-1013333726 |
|
``` |
|
|
|
Or Python API: |
|
|
|
``` |
|
from transformers import AutoModelForSequenceClassification, AutoTokenizer |
|
|
|
model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-mlsec-1013333726", use_auth_token=True) |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("deepesh0x/autotrain-mlsec-1013333726", use_auth_token=True) |
|
|
|
inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
|
|
|
outputs = model(**inputs) |
|
``` |
