
# Model Trained Using AutoNLP

- Problem type: Entity Extraction
- Model ID: 585716433
- CO2 Emissions (in grams): 2.379476355147211

## Validation Metrics

- Loss: 0.15210922062397003
- Accuracy: 0.9724770642201835
- Precision: 0.950836820083682
- Recall: 0.9625838333921638
- F1: 0.9566742676723382

## 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/kSaluja/autonlp-tele_red_data_model-585716433
```

Or Python API:

```
from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("kSaluja/autonlp-tele_red_data_model-585716433", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("kSaluja/autonlp-tele_red_data_model-585716433", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["kSaluja/autonlp-data-tele_red_data_model"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 2.379476355147211}
transformers pytorch bert token-classification autonlp en dataset:kSaluja/autonlp-data-tele_red_data_model co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #autonlp #en #dataset-kSaluja/autonlp-data-tele_red_data_model #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Entity Extraction
- Model ID: 585716433
- CO2 Emissions (in grams): 2.379476355147211

## Validation Metrics

- Loss: 0.15210922062397003
- Accuracy: 0.9724770642201835
- Precision: 0.950836820083682
- Recall: 0.9625838333921638
- F1: 0.9566742676723382

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Entity Extraction
- Model ID: 585716433
- CO2 Emissions (in grams): 2.379476355147211 ## Validation Metrics

- Loss: 0.15210922062397003
- Accuracy: 0.9724770642201835
- Precision: 0.950836820083682
- Recall: 0.9625838333921638
- F1: 0.9566742676723382 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #token-classification #autonlp #en #dataset-kSaluja/autonlp-data-tele_red_data_model #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoNLP

- Problem type: Entity Extraction
- Model ID: 585716433
- CO2 Emissions (in grams): 2.379476355147211 ## Validation Metrics

- Loss: 0.15210922062397003
- Accuracy: 0.9724770642201835
- Precision: 0.950836820083682
- Recall: 0.9625838333921638
- F1: 0.9566742676723382 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #token-classification #autonlp #en #dataset-kSaluja/autonlp-data-tele_red_data_model #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoNLP

- Problem type: Entity Extraction
- Model ID: 585716433
- CO2 Emissions (in grams): 2.379476355147211## Validation Metrics

- Loss: 0.15210922062397003
- Accuracy: 0.9724770642201835
- Precision: 0.950836820083682
- Recall: 0.9625838333921638
- F1: 0.9566742676723382## Usage

You can use cURL to access this model:



Or Python API: