README.md

metadata

tags:
  - autotrain
  - token-classification
language:
  - unk
widget:
  - text: >-
      I’m sorry but I just can’t seem to wrap my head around it. - I’m sorry but
      I just can’t seem to understand.
  - text: Why are you so bent out of shape? - Why are you so upset?
  - text: Listen, it is easier said than done, many people lack commitment.
datasets:
  - imranraad/autotrain-data-magpie-metaphor-xlmr
co2_eq_emissions:
  emissions: 9.232131148683266

Fine-tune datasets

• MAGPIE corpus: https://aclanthology.org/2020.lrec-1.35/

Model Trained Using AutoTrain

• Problem type: Entity Extraction
• Model ID: 1590556166
• CO2 Emissions (in grams): 9.2321

Validation Metrics

• Loss: 0.137
• Accuracy: 0.985
• Precision: 0.000
• Recall: 0.000
• F1: 0.000

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/imranraad/autotrain-magpie-metaphor-xlmr-1590556166

Or Python API:

from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("imranraad/autotrain-magpie-metaphor-xlmr-1590556166", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("imranraad/autotrain-magpie-metaphor-xlmr-1590556166", use_auth_token=True)

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

outputs = model(**inputs)