
# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 869827677
- CO2 Emissions (in grams): 4.365496441173981

## Validation Metrics

- Loss: 0.894961416721344
- Accuracy: 0.7411180773249739
- Precision: 0.590625
- Recall: 0.5080645161290323
- F1: 0.546242774566474

## 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/pujaburman30/autotrain-hi_ner_xlmr-869827677
```

Or Python API:

```
from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("pujaburman30/autotrain-hi_ner_xlmr-869827677", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("pujaburman30/autotrain-hi_ner_xlmr-869827677", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "unk", "tags": "autotrain", "datasets": ["pujaburman30/autotrain-data-hi_ner_xlmr"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 4.365496441173981}
transformers pytorch xlm-roberta token-classification autotrain unk dataset:pujaburman30/autotrain-data-hi_ner_xlmr co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #token-classification #autotrain #unk #dataset-pujaburman30/autotrain-data-hi_ner_xlmr #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 869827677
- CO2 Emissions (in grams): 4.365496441173981

## Validation Metrics

- Loss: 0.894961416721344
- Accuracy: 0.7411180773249739
- Precision: 0.590625
- Recall: 0.5080645161290323
- F1: 0.546242774566474

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 869827677
- CO2 Emissions (in grams): 4.365496441173981 ## Validation Metrics

- Loss: 0.894961416721344
- Accuracy: 0.7411180773249739
- Precision: 0.590625
- Recall: 0.5080645161290323
- F1: 0.546242774566474 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #xlm-roberta #token-classification #autotrain #unk #dataset-pujaburman30/autotrain-data-hi_ner_xlmr #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 869827677
- CO2 Emissions (in grams): 4.365496441173981 ## Validation Metrics

- Loss: 0.894961416721344
- Accuracy: 0.7411180773249739
- Precision: 0.590625
- Recall: 0.5080645161290323
- F1: 0.546242774566474 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #xlm-roberta #token-classification #autotrain #unk #dataset-pujaburman30/autotrain-data-hi_ner_xlmr #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 869827677
- CO2 Emissions (in grams): 4.365496441173981## Validation Metrics

- Loss: 0.894961416721344
- Accuracy: 0.7411180773249739
- Precision: 0.590625
- Recall: 0.5080645161290323
- F1: 0.546242774566474## Usage

You can use cURL to access this model:



Or Python API: