metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Sachinkelenjaguri/autotrain-data-climate-tcfd-recommendation
co2_eq_emissions:
  emissions: 0.0015416078395342335

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 55122128742
CO2 Emissions (in grams): 0.0015

Validation Metrics

Loss: 0.646
Accuracy: 0.777
Macro F1: 0.727
Micro F1: 0.777
Weighted F1: 0.779
Macro Precision: 0.734
Micro Precision: 0.777
Weighted Precision: 0.786
Macro Recall: 0.731
Micro Recall: 0.777
Weighted Recall: 0.777

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/Sachinkelenjaguri/autotrain-climate-tcfd-recommendation-55122128742

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Sachinkelenjaguri/autotrain-climate-tcfd-recommendation-55122128742", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Sachinkelenjaguri/autotrain-climate-tcfd-recommendation-55122128742", use_auth_token=True)

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

outputs = model(**inputs)