metadata

tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: >-
      A new model offers an explanation for how the Galilean satellites formed
      around the solar system’s largest world. Konstantin Batygin did not set
      out to solve one of the solar system’s most puzzling mysteries when he
      went for a run up a hill in Nice, France. Dr. Batygin, a Caltech
      researcher
datasets:
  - AyoubChLin/autotrain-data-anymodel_bbc
  - SetFit/bbc-news
co2_eq_emissions:
  emissions: 2.359134715120443
license: apache-2.0
metrics:
  - accuracy
pipeline_tag: text-classification

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 48900118383
CO2 Emissions (in grams): 2.3591

Validation Metrics

Loss: 0.116
Accuracy: 0.978
Macro F1: 0.978
Micro F1: 0.978
Weighted F1: 0.978
Macro Precision: 0.978
Micro Precision: 0.978
Weighted Precision: 0.978
Macro Recall: 0.978
Micro Recall: 0.978
Weighted Recall: 0.978

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/AyoubChLin/autotrain-anymodel_bbc-48900118383

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/autotrain-anymodel_bbc-48900118383", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/autotrain-anymodel_bbc-48900118383", use_auth_token=True)

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

outputs = model(**inputs)