---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- pujaburman30/autotrain-data-hi_ner_xlmr_large
co2_eq_emissions: 5.880084418778246
---

# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 924630372
- CO2 Emissions (in grams): 5.880084418778246

## Validation Metrics

- Loss: 0.8206124901771545
- Accuracy: 0.7745009890307498
- Precision: 0.6042857142857143
- Recall: 0.6547987616099071
- F1: 0.6285289747399703

## 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_large-924630372
```

Or Python API:

```
from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("pujaburman30/autotrain-hi_ner_xlmr_large-924630372", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("pujaburman30/autotrain-hi_ner_xlmr_large-924630372", use_auth_token=True)

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

outputs = model(**inputs)
```