metadata
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: I love AutoTrain 🤗
datasets:
- davis901/autotrain-data-imdb-textclassification
co2_eq_emissions:
emissions: 3.313265712444502
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 46471115134
- CO2 Emissions (in grams): 3.3133
Validation Metrics
- Loss: 0.006
- Accuracy: 0.999
- Precision: 0.999
- Recall: 1.000
- AUC: 1.000
- F1: 0.999
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/davis901/autotrain-imdb-textclassification-46471115134
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("davis901/autotrain-imdb-textclassification-46471115134", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("davis901/autotrain-imdb-textclassification-46471115134", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)