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HassanDataSci
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Update app.py
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app.py
CHANGED
@@ -1,11 +1,8 @@
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import streamlit as st
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from transformers import pipeline
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from PIL import Image
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import os
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# Hugging Face token login (add this as a secret in Hugging Face Spaces)
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os.environ["HF_TOKEN"] = st.secrets["HF_AUTH_TOKEN"]
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# Load the image classification pipeline
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@st.cache_resource
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def load_image_classification_pipeline():
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@@ -16,22 +13,20 @@ def load_image_classification_pipeline():
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pipe_classification = load_image_classification_pipeline()
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# Load the
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@st.cache_resource
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def load_llama_pipeline():
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"""
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Load the
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"""
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model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct", use_auth_token=os.environ["HF_TOKEN"])
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return pipeline("text-generation", model=model, tokenizer=tokenizer)
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pipe_llama = load_llama_pipeline()
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# Function to generate ingredients using
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def get_ingredients_llama(food_name):
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"""
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Generate a list of ingredients for the given food item using
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"""
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prompt = f"List the main ingredients typically used to prepare {food_name}."
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try:
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@@ -49,7 +44,7 @@ st.image("IR_IMAGE.png", caption="Food Recognition Model", use_column_width=True
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# Sidebar for model information
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st.sidebar.title("Model Information")
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st.sidebar.write("**Image Classification Model**: Shresthadev403/food-image-classification")
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st.sidebar.write("**LLM for Ingredients**:
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# Upload image
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uploaded_file = st.file_uploader("Choose a food image...", type=["jpg", "png", "jpeg"])
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import streamlit as st
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from transformers import pipeline
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from PIL import Image
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import os
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# Load the image classification pipeline
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@st.cache_resource
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def load_image_classification_pipeline():
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pipe_classification = load_image_classification_pipeline()
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# Load the GPT-Neo model for ingredient generation
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@st.cache_resource
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def load_llama_pipeline():
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"""
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Load the GPT-Neo model for ingredient generation.
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"""
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return pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")
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pipe_llama = load_llama_pipeline()
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# Function to generate ingredients using GPT-Neo
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def get_ingredients_llama(food_name):
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"""
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Generate a list of ingredients for the given food item using GPT-Neo.
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"""
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prompt = f"List the main ingredients typically used to prepare {food_name}."
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try:
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# Sidebar for model information
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st.sidebar.title("Model Information")
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st.sidebar.write("**Image Classification Model**: Shresthadev403/food-image-classification")
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st.sidebar.write("**LLM for Ingredients**: EleutherAI/gpt-neo-1.3B")
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# Upload image
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uploaded_file = st.file_uploader("Choose a food image...", type=["jpg", "png", "jpeg"])
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