|
--- |
|
tags: autonlp |
|
language: en |
|
widget: |
|
- text: "I love AutoNLP 🤗" |
|
datasets: |
|
- Harshveer/autonlp-data-formality_scoring_2 |
|
co2_eq_emissions: 8.655894631203154 |
|
--- |
|
|
|
# Model Trained Using AutoNLP |
|
|
|
- Problem type: Single Column Regression |
|
- Model ID: 32597818 |
|
- CO2 Emissions (in grams): 8.655894631203154 |
|
|
|
## Validation Metrics |
|
|
|
- Loss: 0.5410276651382446 |
|
- MSE: 0.5410276651382446 |
|
- MAE: 0.5694561004638672 |
|
- R2: 0.6830431129198475 |
|
- RMSE: 0.735545814037323 |
|
- Explained Variance: 0.6834385395050049 |
|
|
|
## 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/Harshveer/autonlp-formality_scoring_2-32597818 |
|
``` |
|
|
|
Or Python API: |
|
|
|
``` |
|
from transformers import AutoModelForSequenceClassification, AutoTokenizer |
|
|
|
model = AutoModelForSequenceClassification.from_pretrained("Harshveer/autonlp-formality_scoring_2-32597818", use_auth_token=True) |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("Harshveer/autonlp-formality_scoring_2-32597818", use_auth_token=True) |
|
|
|
inputs = tokenizer("I love AutoNLP", return_tensors="pt") |
|
|
|
outputs = model(**inputs) |
|
``` |
