
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Dataset: 1:1 (unknotted : knotted)
- Model ID: 1315550258
- CO2 Emissions (in grams): 0.0216

## Validation Metrics

- Loss: 0.391
- Accuracy: 0.833
- Precision: 0.836
- Recall: 0.823
- AUC: 0.900
- F1: 0.829

## 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/dav3794/autotrain-demo-knots2-1315550258
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("dav3794/autotrain-demo-knots2-1315550258", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("dav3794/autotrain-demo-knots2-1315550258", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["dav3794/autotrain-data-demo-knots2"], "widget": [{"text": "AA sequence with spaces"}], "co2_eq_emissions": {"emissions": 0.021557396511961088}}
transformers pytorch bert text-classification autotrain unk dataset:dav3794/autotrain-data-demo-knots2 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-dav3794/autotrain-data-demo-knots2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Dataset: 1:1 (unknotted : knotted)
- Model ID: 1315550258
- CO2 Emissions (in grams): 0.0216

## Validation Metrics

- Loss: 0.391
- Accuracy: 0.833
- Precision: 0.836
- Recall: 0.823
- AUC: 0.900
- F1: 0.829

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Dataset: 1:1 (unknotted : knotted)
- Model ID: 1315550258
- CO2 Emissions (in grams): 0.0216 ## Validation Metrics

- Loss: 0.391
- Accuracy: 0.833
- Precision: 0.836
- Recall: 0.823
- AUC: 0.900
- F1: 0.829 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-dav3794/autotrain-data-demo-knots2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Dataset: 1:1 (unknotted : knotted)
- Model ID: 1315550258
- CO2 Emissions (in grams): 0.0216 ## Validation Metrics

- Loss: 0.391
- Accuracy: 0.833
- Precision: 0.836
- Recall: 0.823
- AUC: 0.900
- F1: 0.829 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-dav3794/autotrain-data-demo-knots2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Dataset: 1:1 (unknotted : knotted)
- Model ID: 1315550258
- CO2 Emissions (in grams): 0.0216## Validation Metrics

- Loss: 0.391
- Accuracy: 0.833
- Precision: 0.836
- Recall: 0.823
- AUC: 0.900
- F1: 0.829## Usage

You can use cURL to access this model:



Or Python API: