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Model: prithivMLmods/Gliese-OCR-7B-Post1.0 Source: Original Platform
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "DgpubXociwNK"
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},
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"source": [
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"## **Gliese-OCR-7B-Post1.0(4-bit)**"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "Nb3wNhothvX7"
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},
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"source": [
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"The Gliese-OCR-7B-Post1.0 model is a fine-tuned version of Camel-Doc-OCR-062825, optimized for Document Retrieval, Content Extraction, and Analysis Recognition. Built on top of the Qwen2.5-VL architecture, this model enhances document comprehension capabilities with focused training on the Opendoc2-Analysis-Recognition dataset for superior document analysis and information extraction tasks.\n",
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"\n",
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" > This model shows significant improvements in LaTeX rendering and Markdown rendering for OCR tasks.\n",
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"\n",
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"| Image1 | Image2 |\n",
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"|--------|--------|\n",
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"|  |  |\n",
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"\n",
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"*multimodal model & notebook by: [prithivMLmods](https://huggingface.co/prithivMLmods)*"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "Mk560Wx0j6PY"
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},
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"source": [
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"### **Install packages**"
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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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"id": "qTD_dNliNS5T"
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},
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"outputs": [],
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"source": [
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"%%capture\n",
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"!pip install git+https://github.com/huggingface/transformers.git \\\n",
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" git+https://github.com/huggingface/accelerate.git \\\n",
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" git+https://github.com/huggingface/peft.git \\\n",
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" transformers-stream-generator huggingface_hub albumentations \\\n",
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" pyvips-binary qwen-vl-utils sentencepiece opencv-python docling-core \\\n",
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" python-docx torchvision safetensors matplotlib num2words \\\n",
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"\n",
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"!pip install xformers requests pymupdf hf_xet spaces pyvips pillow gradio \\\n",
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" einops torch fpdf timm av decord bitsandbytes reportlab\n",
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"#Hold tight, this will take around 1-2 minutes."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "uiBblyf-kLmf"
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},
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"source": [
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"### **Run Demo App**"
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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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"id": "pgz93DfvNMfb"
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},
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"outputs": [],
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"source": [
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"import spaces\n",
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"import json\n",
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"import math\n",
|
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"import os\n",
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"import traceback\n",
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"from io import BytesIO\n",
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"from typing import Any, Dict, List, Optional, Tuple\n",
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"import re\n",
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"import time\n",
|
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"from threading import Thread\n",
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"from io import BytesIO\n",
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"import uuid\n",
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"import tempfile\n",
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"\n",
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"import gradio as gr\n",
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"import requests\n",
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"import torch\n",
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"from PIL import Image\n",
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"import fitz\n",
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"import numpy as np\n",
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"\n",
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"# --- New Model Imports ---\n",
|
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"from transformers import (\n",
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" Qwen2_5_VLForConditionalGeneration,\n",
|
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" AutoProcessor,\n",
|
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" TextIteratorStreamer,\n",
|
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" BitsAndBytesConfig,\n",
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")\n",
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"\n",
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"from reportlab.lib.pagesizes import A4\n",
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"from reportlab.lib.styles import getSampleStyleSheet\n",
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"from reportlab.platypus import SimpleDocTemplate, Image as RLImage, Paragraph, Spacer\n",
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"from reportlab.lib.units import inch\n",
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"\n",
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"# --- Constants and Model Setup ---\n",
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"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
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"\n",
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"print(\"CUDA_VISIBLE_DEVICES=\", os.environ.get(\"CUDA_VISIBLE_DEVICES\"))\n",
|
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"print(\"torch.__version__ =\", torch.__version__)\n",
|
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"print(\"torch.version.cuda =\", torch.version.cuda)\n",
|
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"print(\"cuda available:\", torch.cuda.is_available())\n",
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"print(\"cuda device count:\", torch.cuda.device_count())\n",
|
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"if torch.cuda.is_available():\n",
|
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" print(\"current device:\", torch.cuda.current_device())\n",
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" print(\"device name:\", torch.cuda.get_device_name(torch.cuda.current_device()))\n",
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"\n",
|
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"print(\"Using device:\", device)\n",
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"\n",
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"\n",
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"# --- Model Loading (Updated for Qwen2.5-VL) ---\n",
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"\n",
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"# Define model options\n",
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"MODEL_OPTIONS = {\n",
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" \"Gliese-OCR-7B-Post1.0\": \"prithivMLmods/Gliese-OCR-7B-Post1.0\",\n",
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"}\n",
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"\n",
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"# Define 4-bit quantization configuration\n",
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"# This config will load the model in 4-bit to save VRAM.\n",
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"quantization_config = BitsAndBytesConfig(\n",
|
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" load_in_4bit=True,\n",
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" bnb_4bit_compute_dtype=torch.float16,\n",
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" bnb_4bit_quant_type=\"nf4\",\n",
|
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" bnb_4bit_use_double_quant=True,\n",
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")\n",
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"\n",
|
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"# Preload models and processors into CUDA\n",
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"models = {}\n",
|
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"processors = {}\n",
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"for name, model_id in MODEL_OPTIONS.items():\n",
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" print(f\"Loading {name}🤗. This will use 4-bit quantization to save VRAM.\")\n",
|
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" models[name] = Qwen2_5_VLForConditionalGeneration.from_pretrained(\n",
|
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" model_id,\n",
|
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" trust_remote_code=True,\n",
|
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" quantization_config=quantization_config,\n",
|
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" device_map=\"auto\"\n",
|
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" )\n",
|
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" processors[name] = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)\n",
|
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"print(\"Model loaded successfully.\")\n",
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"\n",
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"\n",
|
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"# --- PDF Generation and Preview Utility Function (Unchanged) ---\n",
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"def generate_and_preview_pdf(image: Image.Image, text_content: str, font_size: int, line_spacing: float, alignment: str, image_size: str):\n",
|
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" \"\"\"\n",
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" Generates a PDF, saves it, and then creates image previews of its pages.\n",
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" Returns the path to the PDF and a list of paths to the preview images.\n",
|
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" \"\"\"\n",
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" if image is None or not text_content or not text_content.strip():\n",
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" raise gr.Error(\"Cannot generate PDF. Image or text content is missing.\")\n",
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"\n",
|
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" # --- 1. Generate the PDF ---\n",
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" temp_dir = tempfile.gettempdir()\n",
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" pdf_filename = os.path.join(temp_dir, f\"output_{uuid.uuid4()}.pdf\")\n",
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" doc = SimpleDocTemplate(\n",
|
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" pdf_filename,\n",
|
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" pagesize=A4,\n",
|
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" rightMargin=inch, leftMargin=inch,\n",
|
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" topMargin=inch, bottomMargin=inch\n",
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" )\n",
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" styles = getSampleStyleSheet()\n",
|
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" style_normal = styles[\"Normal\"]\n",
|
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" style_normal.fontSize = int(font_size)\n",
|
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" style_normal.leading = int(font_size) * line_spacing\n",
|
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" style_normal.alignment = {\"Left\": 0, \"Center\": 1, \"Right\": 2, \"Justified\": 4}[alignment]\n",
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"\n",
|
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" story = []\n",
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"\n",
|
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" img_buffer = BytesIO()\n",
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" image.save(img_buffer, format='PNG')\n",
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" img_buffer.seek(0)\n",
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"\n",
|
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" page_width, _ = A4\n",
|
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" available_width = page_width - 2 * inch\n",
|
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" image_widths = {\n",
|
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" \"Small\": available_width * 0.3,\n",
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" \"Medium\": available_width * 0.6,\n",
|
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" \"Large\": available_width * 0.9,\n",
|
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" }\n",
|
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" img_width = image_widths[image_size]\n",
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" # Create a ReportLab Image object, handling potential transparency\n",
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" img = RLImage(img_buffer, width=img_width, height=image.height * (img_width / image.width))\n",
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" story.append(img)\n",
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" story.append(Spacer(1, 12))\n",
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"\n",
|
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" # Clean the text for PDF generation\n",
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" cleaned_text = re.sub(r'#+\\s*', '', text_content).replace(\"*\", \"\")\n",
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" text_paragraphs = cleaned_text.split('\\n')\n",
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"\n",
|
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" for para in text_paragraphs:\n",
|
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" if para.strip():\n",
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" story.append(Paragraph(para, style_normal))\n",
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"\n",
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" doc.build(story)\n",
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"\n",
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" # --- 2. Render PDF pages as images for preview ---\n",
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" preview_images = []\n",
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" try:\n",
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" pdf_doc = fitz.open(pdf_filename)\n",
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" for page_num in range(len(pdf_doc)):\n",
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" page = pdf_doc.load_page(page_num)\n",
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" pix = page.get_pixmap(dpi=150)\n",
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" preview_img_path = os.path.join(temp_dir, f\"preview_{uuid.uuid4()}_p{page_num}.png\")\n",
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" pix.save(preview_img_path)\n",
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" preview_images.append(preview_img_path)\n",
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" pdf_doc.close()\n",
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" except Exception as e:\n",
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" print(f\"Error generating PDF preview: {e}\")\n",
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"\n",
|
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" return pdf_filename, preview_images\n",
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"\n",
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"\n",
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"# --- Core Application Logic (Updated for Qwen2.5-VL with Streaming) ---\n",
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"@spaces.GPU\n",
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"def process_document(\n",
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" image: Image.Image,\n",
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" prompt_input: str,\n",
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" max_new_tokens: int,\n",
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" temperature: float,\n",
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" top_p: float,\n",
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" top_k: int,\n",
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" repetition_penalty: float\n",
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"):\n",
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" \"\"\"\n",
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" Main function that handles model inference for the Qwen model with streaming.\n",
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" This function is a generator, yielding text as it is generated.\n",
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" \"\"\"\n",
|
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" if image is None:\n",
|
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" yield \"Please upload an image.\", \"Please upload an image.\"\n",
|
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" return\n",
|
||||
" if not prompt_input or not prompt_input.strip():\n",
|
||||
" yield \"Please enter a prompt.\", \"Please enter a prompt.\"\n",
|
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" return\n",
|
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"\n",
|
||||
" model_name = \"Gliese-OCR-7B-Post1.0\"\n",
|
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" model = models[model_name]\n",
|
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" processor = processors[model_name]\n",
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"\n",
|
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" messages = [\n",
|
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" {\n",
|
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" \"role\": \"user\",\n",
|
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" \"content\": [\n",
|
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" {\"type\": \"image\", \"image\": image},\n",
|
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" {\"type\": \"text\", \"text\": prompt_input},\n",
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" ],\n",
|
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" }\n",
|
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" ]\n",
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"\n",
|
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" text = processor.apply_chat_template(\n",
|
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" messages, tokenize=False, add_generation_prompt=True\n",
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" )\n",
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" inputs = processor(\n",
|
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" text=[text],\n",
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" images=[image],\n",
|
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" padding=True,\n",
|
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" return_tensors=\"pt\",\n",
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" ).to(\"cuda\")\n",
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"\n",
|
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" streamer = TextIteratorStreamer(\n",
|
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" processor.tokenizer, skip_prompt=True, skip_special_tokens=True\n",
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" )\n",
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"\n",
|
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" generation_kwargs = dict(\n",
|
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" inputs,\n",
|
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" streamer=streamer,\n",
|
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" max_new_tokens=max_new_tokens,\n",
|
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" temperature=temperature,\n",
|
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" top_p=top_p,\n",
|
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" top_k=top_k,\n",
|
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" repetition_penalty=repetition_penalty,\n",
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" do_sample=True if temperature > 0 else False,\n",
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" )\n",
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"\n",
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" thread = Thread(target=model.generate, kwargs=generation_kwargs)\n",
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" thread.start()\n",
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"\n",
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" buffer = \"\"\n",
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" for new_text in streamer:\n",
|
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" buffer += new_text\n",
|
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" # Remove special tokens from the output stream\n",
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" clean_buffer = buffer.replace(\"<|im_end|>\", \"\").replace(\"<|endoftext|>\", \"\")\n",
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" yield clean_buffer, clean_buffer\n",
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"\n",
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"# --- Gradio UI Definition (Updated Title, otherwise unchanged) ---\n",
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"def create_gradio_interface():\n",
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" \"\"\"Builds and returns the Gradio web interface.\"\"\"\n",
|
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" css = \"\"\"\n",
|
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" .main-container { max-width: 1400px; margin: 0 auto; }\n",
|
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" .process-button { border: none !important; color: white !important; font-weight: bold !important; background-color: blue !important;}\n",
|
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" .process-button:hover { background-color: darkblue !important; transform: translateY(-2px) !important; box-shadow: 0 4px 8px rgba(0,0,0,0.2) !important; }\n",
|
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" #gallery { min-height: 400px; }\n",
|
||||
" \"\"\"\n",
|
||||
" with gr.Blocks(theme=\"bethecloud/storj_theme\", css=css) as demo:\n",
|
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" gr.HTML(f\"\"\"\n",
|
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" <div class=\"title\" style=\"text-align: center\">\n",
|
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" <h1>Gliese-OCR-7B-Post1.0 📄</h1>\n",
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" <p style=\"font-size: 1.1em; color: #6b7280; margin-bottom: 0.6em;\">\n",
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" Image Content Extraction and Markdown Rendering </b>\n",
|
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" </p>\n",
|
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" </div>\n",
|
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" \"\"\")\n",
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"\n",
|
||||
" with gr.Row():\n",
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" # Left Column (Inputs)\n",
|
||||
" with gr.Column(scale=1):\n",
|
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" prompt_input = gr.Textbox(label=\"Query Input\", placeholder=\"✦︎ Enter the prompt.\", value=\"Precisely OCR the Image.\")\n",
|
||||
" image_input = gr.Image(label=\"Upload Image\", type=\"pil\", sources=['upload'])\n",
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"\n",
|
||||
" with gr.Accordion(\"Advanced Settings\", open=False):\n",
|
||||
" max_new_tokens = gr.Slider(minimum=64, maximum=2048, value=1024, step=32, label=\"Max New Tokens\")\n",
|
||||
" temperature = gr.Slider(label=\"Temperature\", minimum=0.1, maximum=2.0, step=0.1, value=0.7)\n",
|
||||
" top_p = gr.Slider(label=\"Top-p (nucleus sampling)\", minimum=0.05, maximum=1.0, step=0.05, value=0.9)\n",
|
||||
" top_k = gr.Slider(label=\"Top-k\", minimum=1, maximum=100, step=1, value=50)\n",
|
||||
" repetition_penalty = gr.Slider(label=\"Repetition penalty\", minimum=1.0, maximum=2.0, step=0.05, value=1.1)\n",
|
||||
"\n",
|
||||
" with gr.Accordion(\"PDF Export Settings\", open=False):\n",
|
||||
" font_size = gr.Dropdown(choices=[\"8\", \"10\", \"12\", \"14\", \"16\", \"18\"], value=\"12\", label=\"Font Size\")\n",
|
||||
" line_spacing = gr.Dropdown(choices=[1.0, 1.15, 1.5, 2.0], value=1.15, label=\"Line Spacing\")\n",
|
||||
" alignment = gr.Dropdown(choices=[\"Left\", \"Center\", \"Right\", \"Justified\"], value=\"Justified\", label=\"Text Alignment\")\n",
|
||||
" image_size = gr.Dropdown(choices=[\"Small\", \"Medium\", \"Large\"], value=\"Medium\", label=\"Image Size in PDF\")\n",
|
||||
"\n",
|
||||
" process_btn = gr.Button(\"🚀 Process Image\", variant=\"primary\", elem_classes=[\"process-button\"], size=\"lg\")\n",
|
||||
" clear_btn = gr.Button(\"🗑️ Clear All\", variant=\"secondary\")\n",
|
||||
"\n",
|
||||
" # Right Column (Outputs)\n",
|
||||
" with gr.Column(scale=2):\n",
|
||||
" with gr.Tabs() as tabs:\n",
|
||||
" with gr.Tab(\"📝 Extracted Content\"):\n",
|
||||
" raw_output = gr.Textbox(label=\"Model Output\", interactive=False, lines=15, show_copy_button=True)\n",
|
||||
"\n",
|
||||
" gr.Markdown(\"[prithivMLmods🤗](https://huggingface.co/prithivMLmods)\")\n",
|
||||
"\n",
|
||||
" with gr.Tab(\"📰 Markdown Preview\"):\n",
|
||||
" with gr.Accordion(\"(Result.md)\", open=True):\n",
|
||||
" markdown_output = gr.Markdown()\n",
|
||||
"\n",
|
||||
" with gr.Tab(\"📋 PDF Preview\"):\n",
|
||||
" generate_pdf_btn = gr.Button(\"📄 Generate PDF & Render\", variant=\"primary\")\n",
|
||||
" pdf_output_file = gr.File(label=\"Download Generated PDF\", interactive=False)\n",
|
||||
" pdf_preview_gallery = gr.Gallery(label=\"PDF Page Preview\", show_label=True, elem_id=\"gallery\", columns=2, object_fit=\"contain\", height=\"auto\")\n",
|
||||
"\n",
|
||||
" # Event Handlers\n",
|
||||
" def clear_all_outputs():\n",
|
||||
" return None, \"\", \"Model output will appear here.\", \"\", None, None\n",
|
||||
"\n",
|
||||
" # The .click() event will now stream the output from the generator function\n",
|
||||
" process_btn.click(\n",
|
||||
" fn=process_document,\n",
|
||||
" inputs=[image_input, prompt_input, max_new_tokens, temperature, top_p, top_k, repetition_penalty],\n",
|
||||
" outputs=[raw_output, markdown_output]\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" generate_pdf_btn.click(\n",
|
||||
" fn=generate_and_preview_pdf,\n",
|
||||
" inputs=[image_input, raw_output, font_size, line_spacing, alignment, image_size],\n",
|
||||
" outputs=[pdf_output_file, pdf_preview_gallery]\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" clear_btn.click(\n",
|
||||
" clear_all_outputs,\n",
|
||||
" outputs=[image_input, prompt_input, raw_output, markdown_output, pdf_output_file, pdf_preview_gallery]\n",
|
||||
" )\n",
|
||||
" return demo\n",
|
||||
"\n",
|
||||
"if __name__ == \"__main__\":\n",
|
||||
" demo = create_gradio_interface()\n",
|
||||
" # Use queue() for better handling of multiple users and streaming\n",
|
||||
" demo.queue(max_size=20).launch(share=True, show_error=True)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"accelerator": "GPU",
|
||||
"colab": {
|
||||
"gpuType": "T4",
|
||||
"provenance": []
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
120
README.md
Normal file
120
README.md
Normal file
@@ -0,0 +1,120 @@
|
||||
---
|
||||
license: apache-2.0
|
||||
pipeline_tag: image-text-to-text
|
||||
language:
|
||||
- en
|
||||
- zh
|
||||
base_model:
|
||||
- prithivMLmods/Camel-Doc-OCR-062825
|
||||
library_name: transformers
|
||||
tags:
|
||||
- Document
|
||||
- VLM
|
||||
- OCR
|
||||
- VL
|
||||
- Camel
|
||||
- Openpdf
|
||||
- text-generation-inference
|
||||
- Extraction
|
||||
- Linking
|
||||
- Markdown
|
||||
- Document Digitization
|
||||
- Intelligent Document Processing (IDP)
|
||||
- Intelligent Word Recognition (IWR)
|
||||
- Optical Mark Recognition (OMR)
|
||||
---
|
||||
|
||||
|
||||
|
||||
# **Gliese-OCR-7B-Post1.0**
|
||||
|
||||
> The **Gliese-OCR-7B-Post1.0** model is a fine-tuned version of **[Camel-Doc-OCR-062825](https://huggingface.co/prithivMLmods/Camel-Doc-OCR-062825)**, optimized for **Document Retrieval**, **Content Extraction**, and **Analysis Recognition**. Built on top of the Qwen2.5-VL architecture, this model enhances document comprehension capabilities with focused training on the Opendoc2-Analysis-Recognition dataset for superior document analysis and information extraction tasks.
|
||||
|
||||
> [!note]
|
||||
This model shows significant improvements in [LaTeX rendering and Markdown rendering for OCR tasks](https://huggingface.co/prithivMLmods/Gliese-OCR-7B-Post1.0/blob/main/Gliese-OCR-7B-Post1.0(4-bit)-reportlab/Gliese_OCR_7B_Post1_0(4_bit)_reportlab.ipynb).
|
||||
|
||||
# Key Enhancements
|
||||
|
||||
* **Context-Aware Multimodal Extraction and Linking for Documents**: Advanced capability for understanding document context and establishing connections between multimodal elements within documents.
|
||||
|
||||
* **Enhanced Document Retrieval**: Designed to efficiently locate and extract relevant information from complex document structures and layouts.
|
||||
|
||||
* **Superior Content Extraction**: Optimized for precise extraction of structured and unstructured content from diverse document formats.
|
||||
|
||||
* **Analysis Recognition**: Specialized in recognizing and interpreting analytical content, charts, tables, and visual data representations.
|
||||
|
||||
* **State-of-the-Art Performance Across Resolutions**: Achieves competitive results on OCR and visual QA benchmarks such as DocVQA, MathVista, RealWorldQA, and MTVQA.
|
||||
|
||||
* **Video Understanding up to 20+ minutes**: Supports detailed comprehension of long-duration videos for content summarization, Q\&A, and multi-modal reasoning.
|
||||
|
||||
* **Visually-Grounded Device Interaction**: Enables mobile/robotic device operation via visual inputs and text-based instructions using contextual understanding and decision-making logic.
|
||||
|
||||
# Quick Start with Transformers
|
||||
|
||||
```python
|
||||
from transformers import Qwen2_5_VLForConditionalGeneration, AutoTokenizer, AutoProcessor
|
||||
from qwen_vl_utils import process_vision_info
|
||||
|
||||
model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
|
||||
"prithivMLmods/Gliese-OCR-7B-Post1.0", torch_dtype="auto", device_map="auto"
|
||||
)
|
||||
|
||||
processor = AutoProcessor.from_pretrained("prithivMLmods/Gliese-OCR-7B-Post1.0")
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "image",
|
||||
"image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
|
||||
},
|
||||
{"type": "text", "text": "Describe this image."},
|
||||
],
|
||||
}
|
||||
]
|
||||
|
||||
text = processor.apply_chat_template(
|
||||
messages, tokenize=False, add_generation_prompt=True
|
||||
)
|
||||
image_inputs, video_inputs = process_vision_info(messages)
|
||||
inputs = processor(
|
||||
text=[text],
|
||||
images=image_inputs,
|
||||
videos=video_inputs,
|
||||
padding=True,
|
||||
return_tensors="pt",
|
||||
)
|
||||
inputs = inputs.to("cuda")
|
||||
|
||||
generated_ids = model.generate(**inputs, max_new_tokens=128)
|
||||
generated_ids_trimmed = [
|
||||
out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
|
||||
]
|
||||
output_text = processor.batch_decode(
|
||||
generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
|
||||
)
|
||||
print(output_text)
|
||||
```
|
||||
|
||||
# Intended Use
|
||||
|
||||
This model is intended for:
|
||||
|
||||
* Context-aware multimodal extraction and linking for complex document structures.
|
||||
* High-fidelity document retrieval and content extraction from various document formats.
|
||||
* Analysis recognition of charts, graphs, tables, and visual data representations.
|
||||
* Document-based question answering for educational and enterprise applications.
|
||||
* Extraction and LaTeX formatting of mathematical expressions from printed or handwritten content.
|
||||
* Retrieval and summarization from long documents, slides, and multi-modal inputs.
|
||||
* Multilingual document analysis and structured content extraction for global use cases.
|
||||
* Robotic or mobile automation with vision-guided contextual interaction.
|
||||
|
||||
# Limitations
|
||||
|
||||
* May show degraded performance on extremely low-quality or occluded images.
|
||||
* Not optimized for real-time applications on low-resource or edge devices due to computational demands.
|
||||
* Variable accuracy on uncommon or low-resource languages/scripts.
|
||||
* Long video processing may require substantial memory and is not optimized for streaming applications.
|
||||
* Visual token settings affect performance; suboptimal configurations can impact results.
|
||||
* In rare cases, outputs may contain hallucinated or contextually misaligned information.
|
||||
24
added_tokens.json
Normal file
24
added_tokens.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"</tool_call>": 151658,
|
||||
"<tool_call>": 151657,
|
||||
"<|box_end|>": 151649,
|
||||
"<|box_start|>": 151648,
|
||||
"<|endoftext|>": 151643,
|
||||
"<|file_sep|>": 151664,
|
||||
"<|fim_middle|>": 151660,
|
||||
"<|fim_pad|>": 151662,
|
||||
"<|fim_prefix|>": 151659,
|
||||
"<|fim_suffix|>": 151661,
|
||||
"<|im_end|>": 151645,
|
||||
"<|im_start|>": 151644,
|
||||
"<|image_pad|>": 151655,
|
||||
"<|object_ref_end|>": 151647,
|
||||
"<|object_ref_start|>": 151646,
|
||||
"<|quad_end|>": 151651,
|
||||
"<|quad_start|>": 151650,
|
||||
"<|repo_name|>": 151663,
|
||||
"<|video_pad|>": 151656,
|
||||
"<|vision_end|>": 151653,
|
||||
"<|vision_pad|>": 151654,
|
||||
"<|vision_start|>": 151652
|
||||
}
|
||||
7
chat_template.jinja
Normal file
7
chat_template.jinja
Normal file
@@ -0,0 +1,7 @@
|
||||
{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system
|
||||
You are a helpful assistant.<|im_end|>
|
||||
{% endif %}<|im_start|>{{ message['role'] }}
|
||||
{% if message['content'] is string %}{{ message['content'] }}<|im_end|>
|
||||
{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>
|
||||
{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant
|
||||
{% endif %}
|
||||
136
config.json
Normal file
136
config.json
Normal file
@@ -0,0 +1,136 @@
|
||||
{
|
||||
"architectures": [
|
||||
"Qwen2_5_VLForConditionalGeneration"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 3584,
|
||||
"image_token_id": 151655,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 18944,
|
||||
"max_position_embeddings": 128000,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen2_5_vl",
|
||||
"num_attention_heads": 28,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 4,
|
||||
"pad_token_id": 151643,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": {
|
||||
"mrope_section": [
|
||||
16,
|
||||
24,
|
||||
24
|
||||
],
|
||||
"rope_type": "default",
|
||||
"type": "default"
|
||||
},
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": 32768,
|
||||
"text_config": {
|
||||
"architectures": [
|
||||
"Qwen2_5_VLForConditionalGeneration"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 3584,
|
||||
"image_token_id": null,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 18944,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 128000,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen2_5_vl_text",
|
||||
"num_attention_heads": 28,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 4,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": {
|
||||
"mrope_section": [
|
||||
16,
|
||||
24,
|
||||
24
|
||||
],
|
||||
"rope_type": "default",
|
||||
"type": "default"
|
||||
},
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"torch_dtype": "bfloat16",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"video_token_id": null,
|
||||
"vision_end_token_id": 151653,
|
||||
"vision_start_token_id": 151652,
|
||||
"vision_token_id": 151654,
|
||||
"vocab_size": 152064
|
||||
},
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.57.0.dev0",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"video_token_id": 151656,
|
||||
"vision_config": {
|
||||
"depth": 32,
|
||||
"fullatt_block_indexes": [
|
||||
7,
|
||||
15,
|
||||
23,
|
||||
31
|
||||
],
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 1280,
|
||||
"in_channels": 3,
|
||||
"in_chans": 3,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 3420,
|
||||
"model_type": "qwen2_5_vl",
|
||||
"num_heads": 16,
|
||||
"out_hidden_size": 3584,
|
||||
"patch_size": 14,
|
||||
"spatial_merge_size": 2,
|
||||
"spatial_patch_size": 14,
|
||||
"temporal_patch_size": 2,
|
||||
"tokens_per_second": 2,
|
||||
"torch_dtype": "bfloat16",
|
||||
"window_size": 112
|
||||
},
|
||||
"vision_end_token_id": 151653,
|
||||
"vision_start_token_id": 151652,
|
||||
"vision_token_id": 151654,
|
||||
"vocab_size": 152064
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "others", "allow_remote": true}
|
||||
14
generation_config.json
Normal file
14
generation_config.json
Normal file
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"attn_implementation": "flash_attention_2",
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"max_length": 128000,
|
||||
"pad_token_id": 151643,
|
||||
"repetition_penalty": 1.05,
|
||||
"temperature": 1e-06,
|
||||
"transformers_version": "4.54.0"
|
||||
}
|
||||
3
merges.txt
Normal file
3
merges.txt
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:b8e04af9c950e393054010dcef499c3f005e803e9b2da1a09b96a26c33266eb1
|
||||
size 1823241
|
||||
3
model-00001-of-00004.safetensors
Normal file
3
model-00001-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:ac9baf0d8f1bbd4c830305ee7b0ad0aabc627faf285264ad37dc3ac5328f4e82
|
||||
size 4968243304
|
||||
3
model-00002-of-00004.safetensors
Normal file
3
model-00002-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
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209
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|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "right",
|
||||
"processor_class": "Qwen2_5_VLProcessor",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
43
video_preprocessor_config.json
Normal file
43
video_preprocessor_config.json
Normal file
@@ -0,0 +1,43 @@
|
||||
{
|
||||
"crop_size": null,
|
||||
"data_format": "channels_first",
|
||||
"default_to_square": true,
|
||||
"device": null,
|
||||
"do_center_crop": null,
|
||||
"do_convert_rgb": true,
|
||||
"do_normalize": true,
|
||||
"do_pad": null,
|
||||
"do_rescale": true,
|
||||
"do_resize": true,
|
||||
"do_sample_frames": false,
|
||||
"fps": null,
|
||||
"image_mean": [
|
||||
0.48145466,
|
||||
0.4578275,
|
||||
0.40821073
|
||||
],
|
||||
"image_std": [
|
||||
0.26862954,
|
||||
0.26130258,
|
||||
0.27577711
|
||||
],
|
||||
"input_data_format": null,
|
||||
"max_frames": 768,
|
||||
"max_pixels": 12845056,
|
||||
"merge_size": 2,
|
||||
"min_frames": 4,
|
||||
"min_pixels": 3136,
|
||||
"num_frames": null,
|
||||
"patch_size": 14,
|
||||
"processor_class": "Qwen2_5_VLProcessor",
|
||||
"resample": 3,
|
||||
"rescale_factor": 0.00392156862745098,
|
||||
"size": {
|
||||
"longest_edge": 12845056,
|
||||
"shortest_edge": 3136
|
||||
},
|
||||
"size_divisor": null,
|
||||
"temporal_patch_size": 2,
|
||||
"video_metadata": null,
|
||||
"video_processor_type": "Qwen2VLVideoProcessor"
|
||||
}
|
||||
BIN
vocab.json
(Stored with Git LFS)
Normal file
BIN
vocab.json
(Stored with Git LFS)
Normal file
Binary file not shown.
Reference in New Issue
Block a user