Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+from diffusers import StableDiffusionPipeline, AutoencoderKL
+from torchvision import models
+
+tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-multi")
+model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-multi")
+pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
+video_model = models.resnet50(pretrained=True)
+st.title("FallnAI Inference App")
+st.subheader("Coding Model")
+user_input = st.text_input("Enter your code:")
+if st.button("Generate"):
+    result = pipeline("text-generation", model=model, tokenizer=tokenizer)(user_input)
+    st.write(result[0]['generated_text'])
+st.subheader("Stable Diffusion Model")
+prompt = st.text_input("Enter your prompt:")
+if st.button("Generate"):
+    image = pipe(prompt).images[0]
+    st.image(image)
+st.subheader("Video Model")
+video_file = st.file_uploader("Upload a video file:", type=["mp4", "avi"])
+if video_file is not None:
+    video_bytes = video_file.getvalue()
+    st.video(video_bytes)
+    video_transformed = video_model(video_bytes)
+
+