
# 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)
```
{"language": "en", "tags": "autonlp", "datasets": ["Harshveer/autonlp-data-formality_scoring_2"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 8.655894631203154}
transformers pytorch roberta text-classification autonlp en dataset:Harshveer/autonlp-data-formality_scoring_2 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autonlp #en #dataset-Harshveer/autonlp-data-formality_scoring_2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# 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:



Or Python API:


# 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:



Or Python API:
TAGS
#transformers #pytorch #roberta #text-classification #autonlp #en #dataset-Harshveer/autonlp-data-formality_scoring_2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # 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:



Or Python API:
passage: TAGS
#transformers #pytorch #roberta #text-classification #autonlp #en #dataset-Harshveer/autonlp-data-formality_scoring_2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# 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:



Or Python API: