
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3547495705
- CO2 Emissions (in grams): 54.7828

## Validation Metrics

- Loss: 0.226
- Accuracy: 0.948
- Precision: 0.945
- Recall: 0.952
- AUC: 0.986
- F1: 0.948

## 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/kkmkorea/autotrain-patentmatch-3547495705
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("kkmkorea/autotrain-patentmatch-3547495705", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("kkmkorea/autotrain-patentmatch-3547495705", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["en"], "tags": ["autotrain", "text-classification"], "datasets": ["kkmkorea/autotrain-data-patentmatch"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 54.78280971868554}}
transformers pytorch deberta text-classification autotrain en dataset:kkmkorea/autotrain-data-patentmatch co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #deberta #text-classification #autotrain #en #dataset-kkmkorea/autotrain-data-patentmatch #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3547495705
- CO2 Emissions (in grams): 54.7828

## Validation Metrics

- Loss: 0.226
- Accuracy: 0.948
- Precision: 0.945
- Recall: 0.952
- AUC: 0.986
- F1: 0.948

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3547495705
- CO2 Emissions (in grams): 54.7828 ## Validation Metrics

- Loss: 0.226
- Accuracy: 0.948
- Precision: 0.945
- Recall: 0.952
- AUC: 0.986
- F1: 0.948 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #deberta #text-classification #autotrain #en #dataset-kkmkorea/autotrain-data-patentmatch #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 3547495705
- CO2 Emissions (in grams): 54.7828 ## Validation Metrics

- Loss: 0.226
- Accuracy: 0.948
- Precision: 0.945
- Recall: 0.952
- AUC: 0.986
- F1: 0.948 ## Usage

You can use cURL to access this model:



Or Python API: