metadata
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: I love AutoTrain 🤗
datasets:
- sasha/autotrain-data-roberta-base-imdb
co2_eq_emissions:
emissions: 0.40076315373894394
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1275248775
- CO2 Emissions (in grams): 0.4008
Validation Metrics
- Loss: 0.167
- Accuracy: 0.948
- Precision: 0.947
- Recall: 0.948
- AUC: 0.988
- F1: 0.948
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/sasha/autotrain-roberta-base-imdb-1275248775
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("sasha/autotrain-roberta-base-imdb-1275248775", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("sasha/autotrain-roberta-base-imdb-1275248775", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)