Instructions to use Rizky2Hero/Gender_Identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rizky2Hero/Gender_Identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Rizky2Hero/Gender_Identification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Rizky2Hero/Gender_Identification") model = AutoModelForImageClassification.from_pretrained("Rizky2Hero/Gender_Identification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 631 Bytes
c06efae | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | from flask import Flask, request, jsonify
app = Flask(__name__)
@app.route('/predict', methods=['POST'])
def predict():
# Ambil gambar yang diunggah oleh pengguna
uploaded_image = request.files['image']
# Lakukan inferensi dengan model Hugging Face di sini
# gantilah ini dengan kode yang sesuai dengan model Anda
# Misalnya, Anda dapat menggunakan model yang telah di-host di Hugging Face:
# result = your_huggingface_model.predict(uploaded_image)
# Kembalikan hasil inferensi ke pengguna
return jsonify({'result': 'prediction_result'})
if __name__ == '__main__':
app.run(debug=True)
|