
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3522695252
- CO2 Emissions (in grams): 0.1275

## Validation Metrics

- Loss: 0.000
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000

## 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/davanstrien/autotrain-dataset-mentions-160223-3522695252
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("davanstrien/autotrain-dataset-mentions-160223-3522695252", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-dataset-mentions-160223-3522695252", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)
```
{"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["autotrain", "text-classification"], "datasets": ["librarian-bots/model_card_dataset_mentions"], "metrics": ["f1", "accuracy", "recall"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.12753465619151655}, "pipeline_tag": "text-classification"}
transformers pytorch safetensors bert text-classification autotrain en dataset:librarian-bots/model_card_dataset_mentions license:mit co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #text-classification #autotrain #en #dataset-librarian-bots/model_card_dataset_mentions #license-mit #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3522695252
- CO2 Emissions (in grams): 0.1275

## Validation Metrics

- Loss: 0.000
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3522695252
- CO2 Emissions (in grams): 0.1275 ## Validation Metrics

- Loss: 0.000
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #safetensors #bert #text-classification #autotrain #en #dataset-librarian-bots/model_card_dataset_mentions #license-mit #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3522695252
- CO2 Emissions (in grams): 0.1275 ## Validation Metrics

- Loss: 0.000
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #safetensors #bert #text-classification #autotrain #en #dataset-librarian-bots/model_card_dataset_mentions #license-mit #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3522695252
- CO2 Emissions (in grams): 0.1275## Validation Metrics

- Loss: 0.000
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000## Usage

You can use cURL to access this model:



Or Python API: