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cd7c5fe
1
Parent(s):
579e033
updated app.py
Browse files- app.py +3 -3
- demo.ipynb +0 -134
app.py
CHANGED
@@ -27,7 +27,7 @@ def answer_question(image, question):
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if image is None:
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return "Error: Please upload an image."
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-
# Convert NumPy array to PIL Image
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try:
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if isinstance(image, np.ndarray):
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image = Image.fromarray(image)
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@@ -49,14 +49,14 @@ def answer_question(image, question):
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},
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]
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# Apply chat template
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try:
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prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
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inputs = processor(text=prompt, images=[image], return_tensors="pt").to(DEVICE)
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except Exception as e:
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return f"Error: Failed to prepare inputs. {str(e)}"
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# Generate
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try:
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outputs = model.generate(**inputs, max_new_tokens=400)
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answer = processor.decode(outputs[0], skip_special_tokens=True)
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if image is None:
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return "Error: Please upload an image."
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+
# Convert NumPy array to PIL Image
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try:
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if isinstance(image, np.ndarray):
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image = Image.fromarray(image)
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},
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]
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+
# Apply chat template and prepare inputs
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try:
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prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
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inputs = processor(text=prompt, images=[image], return_tensors="pt").to(DEVICE)
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except Exception as e:
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return f"Error: Failed to prepare inputs. {str(e)}"
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+
# Generate answer
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try:
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outputs = model.generate(**inputs, max_new_tokens=400)
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answer = processor.decode(outputs[0], skip_special_tokens=True)
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demo.ipynb
DELETED
@@ -1,134 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/kask/miniconda3/envs/innovatie-week/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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" from .autonotebook import tqdm as notebook_tqdm\n"
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]
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}
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],
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"source": [
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"from transformers import AutoProcessor, AutoModelForVision2Seq\n",
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"from transformers.image_utils import load_image\n",
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"import numpy as np\n",
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"import gradio as gr\n",
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"import torch\n",
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"from PIL import Image"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"cpu\n"
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]
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}
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],
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"source": [
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"# Set the device (GPU or CPU)\n",
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"DEVICE = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
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"print(DEVICE)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Some kwargs in processor config are unused and will not have any effect: image_seq_len. \n"
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]
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}
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],
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"source": [
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"# Initialize processor and model\n",
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"try:\n",
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" processor = AutoProcessor.from_pretrained(\"HuggingFaceTB/SmolVLM-Instruct\")\n",
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" model = AutoModelForVision2Seq.from_pretrained(\n",
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" \"HuggingFaceTB/SmolVLM-Instruct\",\n",
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" torch_dtype=torch.bfloat16,\n",
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" _attn_implementation=\"flash_attention_2\" if DEVICE == \"cuda\" else \"eager\",).to(DEVICE)\n",
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"except Exception as e:\n",
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" print(f\"Error loading model or processor: {str(e)}\")\n",
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" exit(1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/kask/miniconda3/envs/innovatie-week/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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" from .autonotebook import tqdm as notebook_tqdm\n",
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"Some kwargs in processor config are unused and will not have any effect: image_seq_len. \n"
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]
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},
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{
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"ename": "",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
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"\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
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"\u001b[1;31mClick <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. \n",
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"\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
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]
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}
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],
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"source": [
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"from transformers import AutoProcessor, AutoModelForVision2Seq\n",
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"import tqdm as notebook_tqdm\n",
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"\n",
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"# Define the model name\n",
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"model_name = \"HuggingFaceTB/SmolVLM-Instruct\"\n",
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"\n",
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"# Download and save the processor and model locally\n",
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"processor = AutoProcessor.from_pretrained(model_name)\n",
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"processor.save_pretrained(\"./local_model\")\n",
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"\n",
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"model = AutoModelForVision2Seq.from_pretrained(model_name)\n",
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"model.save_pretrained(\"./local_model\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "innovatie-week",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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