fixed model loading

app.py

@@ -1,17 +1,27 @@
+import keras
 
-import keras_nlp
 import tensorflow as tf
 import gradio as gr
 import json
 import os
+from keras_hub.models import GemmaCausalLM
 
-# Load model configuration
-with open("gemma_finetuned_model/config.json", "r") as f:
+# Path to your locally saved model and config
+model_weights_path = "gemma_finetuned_model/finetunedmodel.weights.h5"
+config_path = "gemma_finetuned_model/config.json"
+
+# Load the model using the local config and weights
+with open(config_path, "r") as f:
     config = json.load(f)
 
-# Load the fine-tuned model
-gemma_lm = keras_nlp.models.GemmaCausalLM.from_preset("gemma_2b_en", **config)
-gemma_lm.load_weights("gemma_finetuned_model/model_weights.h5")
+gemma_lm = GemmaCausalLM.from_config(config)
+gemma_lm.load_weights(model_weights_path)
+
+
+#
+# # Load the fine-tuned model
+# gemma_lm = GemmaCausalLM.from_preset("gemma_2b_en", **config)
+# gemma_lm.load_weights("gemma_finetuned_model/model_weights.h5")
 
 # Gradio app function
 def generate_response(prompt):

requirements.txt

@@ -1,4 +1,4 @@
-
-keras-nlp
+keras
+keras-hub
 tensorflow
 gradio