metadata
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: I love AutoTrain 🤗
datasets:
- sabhashanki/autotrain-data-topic-prediction-latest
co2_eq_emissions:
emissions: 1.6843691621907744
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2396974950
- CO2 Emissions (in grams): 1.6844
Validation Metrics
- Loss: 0.674
- Accuracy: 0.829
- Macro F1: 0.810
- Micro F1: 0.829
- Weighted F1: 0.824
- Macro Precision: 0.838
- Micro Precision: 0.829
- Weighted Precision: 0.842
- Macro Recall: 0.811
- Micro Recall: 0.829
- Weighted Recall: 0.829
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/sabhashanki/autotrain-topic-prediction-latest-2396974950
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("sabhashanki/autotrain-topic-prediction-latest-2396974950", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("sabhashanki/autotrain-topic-prediction-latest-2396974950", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)