README.md

metadata

tags: autotrain
language: unk
widget:
  - text: ACE2 overexpression in AAV cell lines
datasets:
  - Mim/autotrain-data-procell-expert
co2_eq_emissions: 0.004814823138367317

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 800724769
• CO2 Emissions (in grams): 0.004814823138367317

Validation Metrics

• Loss: 0.4749071002006531
• Accuracy: 0.9
• Precision: 0.8928571428571429
• Recall: 0.9615384615384616
• AUC: 0.9065934065934066
• F1: 0.9259259259259259

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/Mim/autotrain-procell-expert-800724769

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Mim/autotrain-procell-expert-800724769", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Mim/autotrain-procell-expert-800724769", use_auth_token=True)

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

outputs = model(**inputs)