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pujaburman30
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autotrain-hi_ner_xlmr_large-924630372

Token Classification
Transformers
PyTorch
Enawené-Nawé
xlm-roberta
Trained with AutoTrain
Carbon Emissions
Inference Endpoints
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autotrain-hi_ner_xlmr_large-924630372 / README.md
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metadata
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)