Delete HauauCS_Abliterated_Qwen_3_5_4B_LLM_model.ipynb

HauauCS_Abliterated_Qwen_3_5_4B_LLM_model.ipynb

@@ -1 +0,0 @@
-{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[{"file_id":"https://huggingface.co/datasets/codeShare/lora-training-data/blob/main/HauauCS_Abliterated_Qwen_3_5_4B_LLM_model.ipynb","timestamp":1794394717019}],"gpuType":"T4"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","source":["# HauauCS Abliterated Qwen 3.5 -4B LLM model (image and/or text input)"],"metadata":{"id":"ewVsp7wRAH2j"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"lC55DC9m_4Zz"},"outputs":[],"source":["\n","# ============================================================\n","# QWEN3.5-4B UNCENSORED - GOOGLE COLAB T4\n","#\n","# Model:\n","# DreamFast/Qwen3.5-4B-Uncensored-HauhauCS-Aggressive-Safetensor-Benchmark\n","#\n","# GPU: NVIDIA T4 16GB\n","# Quantization: BitsAndBytes NF4 4-bit\n","# Compute: FP16\n","# Attention: SDPA\n","#\n","# Features:\n","# - Text and image conversations\n","# - Conversation history\n","# - Separate THINKS and SAYS sections\n","# - Larger Gradio chat interface\n","# - Expandable latest-response panels\n","# - Adjustable generation settings\n","# - HF_TOKEN from Colab Secrets\n","# ============================================================\n","\n","\n","# ============================================================\n","# 1. INSTALL DEPENDENCIES\n","# ============================================================\n","\n","import sys\n","import subprocess\n","\n","# Explicitly upgrade Pillow to ensure correct typing dependencies are resolved.\n","subprocess.run(\n","    [\n","        sys.executable, \"-m\", \"pip\", \"install\", \"-q\", \"-U\",\n","        \"--force-reinstall\",\n","        \"pillow\",\n","        \"bitsandbytes\",\n","        \"accelerate\",\n","        \"transformers\",\n","        \"gradio>=6.0\",\n","        \"huggingface_hub\"\n","    ],\n","    check=True\n",")\n","\n","import transformers\n","# ============================================================\n","# 2. IMPORTS\n","# ============================================================\n","\n","import os\n","import re\n","import gc\n","import torch\n","import gradio as gr\n","\n","from PIL import Image\n","from pathlib import Path\n","\n","from google.colab import userdata\n","\n","from huggingface_hub import hf_hub_download\n","\n","from transformers import (\n","    AutoProcessor,\n","    AutoTokenizer,\n","    AutoModelForMultimodalLM,\n","    BitsAndBytesConfig\n",")\n","\n","\n","# ============================================================\n","# 3. CONFIGURATION\n","# ============================================================\n","\n","MODEL_ID = (\n","    \"DreamFast/\"\n","    \"Qwen3.5-4B-Uncensored-HauhauCS-Aggressive-Safetensor-Benchmark\"\n",")\n","\n","BASE_MODEL_ID = \"Qwen/Qwen3.5-4B\"\n","\n","HF_TOKEN = userdata.get(\"HF_TOKEN\")\n","\n","if not HF_TOKEN:\n","    raise ValueError(\n","        \"HF_TOKEN not found in Colab Secrets. \"\n","        \"Please add your Hugging Face token.\"\n","    )\n","\n","if not torch.cuda.is_available():\n","    raise RuntimeError(\"No CUDA GPU detected.\")\n","\n","print(\"GPU:\", torch.cuda.get_device_name(0))\n","print(\"VRAM:\", round(\n","    torch.cuda.get_device_properties(0).total_memory / 1024**3, 2\n","), \"GB\")\n","\n","torch.backends.cuda.matmul.allow_tf32 = True\n","\n","\n","# ============================================================\n","# 4. LOAD CHAT TEMPLATE\n","# ============================================================\n","\n","print(\"\\nLoading Qwen3.5 tokenizer...\")\n","\n","tokenizer = AutoTokenizer.from_pretrained(\n","    BASE_MODEL_ID,\n","    token=HF_TOKEN,\n","    trust_remote_code=True\n",")\n","\n","if not tokenizer.chat_template:\n","\n","    print(\"Downloading original Qwen3.5 chat template...\")\n","\n","    template_path = hf_hub_download(\n","        repo_id=BASE_MODEL_ID,\n","        filename=\"chat_template.jinja\",\n","        token=HF_TOKEN\n","    )\n","\n","    with open(template_path, \"r\", encoding=\"utf-8\") as f:\n","        chat_template = f.read()\n","\n","    tokenizer.chat_template = chat_template\n","\n","else:\n","    chat_template = tokenizer.chat_template\n","\n","print(\"Chat template loaded.\")\n","\n","\n","# ============================================================\n","# 5. LOAD PROCESSOR\n","# ============================================================\n","\n","print(\"\\nLoading multimodal processor...\")\n","\n","processor = AutoProcessor.from_pretrained(\n","    MODEL_ID,\n","    token=HF_TOKEN,\n","    trust_remote_code=True\n",")\n","\n","# Use the compatible original Qwen3.5 tokenizer/template.\n","processor.tokenizer = tokenizer\n","processor.chat_template = chat_template\n","\n","print(\"Processor loaded.\")\n","\n","\n","# ============================================================\n","# 6. 4-BIT QUANTIZATION\n","# ============================================================\n","\n","quantization_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_quant_type=\"nf4\",\n","    bnb_4bit_compute_dtype=torch.float16,\n","    bnb_4bit_use_double_quant=True\n",")\n","\n","\n","# ============================================================\n","# 7. LOAD MODEL\n","# ============================================================\n","\n","print(\"\\nLoading model in 4-bit...\")\n","\n","model = AutoModelForMultimodalLM.from_pretrained(\n","    MODEL_ID,\n","    token=HF_TOKEN,\n","    quantization_config=quantization_config,\n","    dtype=torch.float16,\n","    device_map=\"auto\",\n","    low_cpu_mem_usage=True,\n","    attn_implementation=\"sdpa\",\n","    trust_remote_code=True\n",")\n","\n","model.eval()\n","\n","print(\"\\nModel loaded successfully.\")\n","\n","print(\"Model device:\", model.get_input_embeddings().weight.device)\n","\n","# ============================================================\n","# 8. PREPARE MULTIMODAL INPUTS\n","# ============================================================\n","\n","def prepare_multimodal_inputs(messages):\n","\n","    # Apply the chat template using the tokenizer directly.\n","    prompt = tokenizer.apply_chat_template(\n","        messages,\n","        tokenize=False,\n","        add_generation_prompt=True\n","    )\n","\n","    # Collect images in conversation order.\n","    images = []\n","\n","    for msg in messages:\n","\n","        content = msg.get(\"content\", [])\n","\n","        if isinstance(content, str):\n","            continue\n","\n","        if not isinstance(content, list):\n","            continue\n","\n","        for item in content:\n","\n","            if (\n","                isinstance(item, dict)\n","                and item.get(\"type\") == \"image\"\n","            ):\n","\n","                image = item.get(\"image\")\n","\n","                if image is not None:\n","                    images.append(image)\n","\n","    # Process text and images.\n","    if images:\n","\n","        formatted_inputs = processor(\n","            text=prompt,\n","            images=images,\n","            return_tensors=\"pt\"\n","        )\n","\n","    else:\n","\n","        formatted_inputs = processor(\n","            text=prompt,\n","            return_tensors=\"pt\"\n","        )\n","\n","    return formatted_inputs\n","\n","\n","# ============================================================\n","# 9. SPLIT THINKING AND FINAL ANSWER\n","# ============================================================\n","\n","def split_thinking_and_answer(raw_text):\n","\n","    \"\"\"\n","    Separates model-generated <think>...</think> content\n","    from the final answer.\n","\n","    If the model does not return a think block, its complete\n","    response is treated as the final answer.\n","    \"\"\"\n","\n","    raw_text = raw_text.strip()\n","\n","    # Remove common trailing generation tokens.\n","    raw_text = re.sub(\n","        r\"<\\|im_end\\|>|<\\|endoftext\\|>|</s>\",\n","        \"\",\n","        raw_text\n","    ).strip()\n","\n","    # Find a complete think block.\n","    match = re.search(\n","        r\"<think>(.*?)</think>\",\n","        raw_text,\n","        flags=re.DOTALL | re.IGNORECASE\n","    )\n","\n","    if match:\n","\n","        thinking = match.group(1).strip()\n","\n","        # Everything outside the think block is the answer.\n","        answer = (\n","            raw_text[:match.start()]\n","            + raw_text[match.end():]\n","        ).strip()\n","\n","    else:\n","\n","        # Handle an unclosed think block.\n","        open_match = re.search(\n","            r\"<think>\",\n","            raw_text,\n","            flags=re.IGNORECASE\n","        )\n","\n","        if open_match:\n","\n","            thinking = raw_text[open_match.end():].strip()\n","            answer = \"\"\n","\n","        else:\n","\n","            thinking = \"The model did not return a separate <think> block.\"\n","            answer = raw_text\n","\n","    # Remove any remaining template artifacts.\n","    answer = re.sub(\n","        r\"<\\|im_start\\|>|<\\|im_sep\\|>|<\\|im_end\\|>\",\n","        \"\",\n","        answer\n","    ).strip()\n","\n","    thinking = re.sub(\n","        r\"<\\|im_start\\|>|<\\|im_sep\\|>|<\\|im_end\\|>\",\n","        \"\",\n","        thinking\n","    ).strip()\n","\n","    if not answer:\n","        answer = \"(The model did not produce a separate final answer.)\"\n","\n","    if not thinking:\n","        thinking = \"(No thinking text was returned.)\"\n","\n","    return thinking, answer\n","\n","\n","# ============================================================\n","# 10. GENERATION FUNCTION\n","# ============================================================\n","\n","def generate_response(\n","    messages,\n","    max_new_tokens=1024,\n","    temperature=0.7,\n","    top_p=0.9\n","):\n","\n","    inputs = prepare_multimodal_inputs(messages)\n","\n","    # Move inputs to the model's embedding device.\n","    input_device = model.get_input_embeddings().weight.device\n","\n","    inputs = inputs.to(input_device)\n","\n","    input_length = inputs[\"input_ids\"].shape[-1]\n","\n","    do_sample = float(temperature) > 0\n","\n","    generation_kwargs = {\n","        \"max_new_tokens\": int(max_new_tokens),\n","        \"do_sample\": do_sample,\n","        \"repetition_penalty\": 1.05,\n","        \"pad_token_id\": tokenizer.pad_token_id\n","            if tokenizer.pad_token_id is not None\n","            else tokenizer.eos_token_id,\n","        \"eos_token_id\": tokenizer.eos_token_id,\n","        \"use_cache\": True\n","    }\n","\n","    if do_sample:\n","\n","        generation_kwargs.update({\n","            \"temperature\": float(temperature),\n","            \"top_p\": float(top_p)\n","        })\n","\n","    with torch.inference_mode():\n","\n","        output_ids = model.generate(\n","            **inputs,\n","            **generation_kwargs\n","        )\n","\n","    # Decode only newly generated tokens.\n","    generated_ids = output_ids[0][input_length:]\n","\n","    raw_response = tokenizer.decode(\n","        generated_ids,\n","        skip_special_tokens=False,\n","        clean_up_tokenization_spaces=False\n","    )\n","\n","    thinking, answer = split_thinking_and_answer(raw_response)\n","\n","    # Keep the original model response in the conversation history.\n","    return raw_response.strip(), thinking, answer\n","\n","\n","# ============================================================\n","# 11. GRADIO CHAT FUNCTION\n","# ============================================================\n","\n","def chat(\n","    message,\n","    image,\n","    chat_history,\n","    conversation_history,\n","    max_new_tokens,\n","    temperature,\n","    top_p\n","):\n","\n","    if chat_history is None:\n","        chat_history = []\n","\n","    if conversation_history is None:\n","        conversation_history = []\n","\n","    message = (message or \"\").strip()\n","\n","    if not message and image is None:\n","\n","        return (\n","            chat_history,\n","            conversation_history,\n","            \"\",\n","            None,\n","            \"\",\n","            \"Please enter a message or upload an image.\"\n","        )\n","\n","    # Build user content.\n","    user_content = []\n","\n","    if message:\n","\n","        user_content.append({\n","            \"type\": \"text\",\n","            \"text\": message\n","        })\n","\n","    if image is not None:\n","\n","        # Convert to RGB PIL image.\n","        if isinstance(image, Image.Image):\n","            image = image.convert(\"RGB\")\n","\n","        user_content.append({\n","            \"type\": \"image\",\n","            \"image\": image\n","        })\n","\n","    # Add user turn to actual model conversation.\n","    conversation_history = list(conversation_history)\n","\n","    conversation_history.append({\n","        \"role\": \"user\",\n","        \"content\": user_content\n","    })\n","\n","    # Display user message in the chat window.\n","    display_message = message if message else \"Please describe this image.\"\n","\n","    if image is not None:\n","        display_message += \"\\n\\n📷 *Image attached*\"\n","\n","    chat_history = list(chat_history)\n","\n","    chat_history.append({\n","        \"role\": \"user\",\n","        \"content\": display_message\n","    })\n","\n","    try:\n","\n","        raw_response, thinking, answer = generate_response(\n","            conversation_history,\n","            max_new_tokens=max_new_tokens,\n","            temperature=temperature,\n","            top_p=top_p\n","        )\n","\n","        # Store the complete response for subsequent turns.\n","        conversation_history.append({\n","            \"role\": \"assistant\",\n","            \"content\": raw_response\n","        })\n","\n","        # Add two separate assistant messages to the chat.\n","        chat_history.append({\n","            \"role\": \"assistant\",\n","            \"content\": \"### 💭 WHAT THE MODEL THINKS\\n\\n\" + thinking\n","        })\n","\n","        chat_history.append({\n","            \"role\": \"assistant\",\n","            \"content\": \"### 🗣️ WHAT THE MODEL SAYS\\n\\n\" + answer\n","        })\n","\n","        return (\n","            chat_history,\n","            conversation_history,\n","            \"\",\n","            None,\n","            thinking,\n","            answer\n","        )\n","\n","    except Exception as e:\n","\n","        error_message = f\"Generation error:\\n\\n{str(e)}\"\n","\n","        chat_history.append({\n","            \"role\": \"assistant\",\n","            \"content\": error_message\n","        })\n","\n","        return (\n","            chat_history,\n","            conversation_history,\n","            message,\n","            image,\n","            \"\",\n","            error_message\n","        )\n","\n","\n","# ============================================================\n","# 12. CLEAR CONVERSATION\n","# ============================================================\n","\n","def clear_chat():\n","\n","    return (\n","        [],\n","        [],\n","        \"\",\n","        None,\n","        \"\",\n","        \"\"\n","    )\n","\n","\n","# ============================================================\n","# 13. GRADIO INTERFACE\n","# ============================================================\n","\n","CUSTOM_CSS = \"\"\"\n","body {\n","    background: #181818 !important;\n","}\n","\n",".gradio-container {\n","    max-width: 1500px !important;\n","    margin: auto !important;\n","}\n","\n","#main-title {\n","    text-align: center;\n","    margin-bottom: 5px;\n","}\n","\n","#chat-window {\n","    min-height: 650px !important;\n","}\n","\n","#chat-window .message {\n","    font-size: 16px !important;\n","    line-height: 1.65 !important;\n","}\n","\n","#message-input textarea {\n","    font-size: 16px !important;\n","    line-height: 1.6 !important;\n","}\n","\n","#thinking-panel textarea,\n","#answer-panel textarea {\n","    font-size: 15px !important;\n","    line-height: 1.7 !important;\n","}\n","\n","#send-button {\n","    background: #a78bfa !important;\n","    color: #181818 !important;\n","    font-weight: bold !important;\n","}\n","\n","#clear-button {\n","    background: #383344 !important;\n","}\n","\"\"\"\n","\n","\n","with gr.Blocks(\n","    theme=gr.themes.Base(\n","        primary_hue=\"violet\",\n","        secondary_hue=\"orange\",\n","        neutral_hue=\"slate\"\n","    ),\n","    css=CUSTOM_CSS,\n","    title=\"Qwen3.5-4B Uncensored Chat\"\n",") as demo:\n","\n","    gr.Markdown(\n","        \"\"\"\n","        # Qwen3.5-4B Uncensored Chat\n","\n","        **DreamFast / HauhauCS — 4-bit NF4 — NVIDIA T4**\n","\n","        Model responses are separated into their generated thinking\n","        section and their final answer.\n","        \"\"\",\n","        elem_id=\"main-title\"\n","    )\n","\n","    # Actual model conversation and displayed chat are separate.\n","    conversation_state = gr.State([])\n","\n","    with gr.Row():\n","\n","        with gr.Column(scale=7):\n","\n","            chatbot = gr.Chatbot(\n","                label=\"Conversation\",\n","                height=650,\n","                autoscroll=True,\n","                elem_id=\"chat-window\"\n","            )\n","\n","            with gr.Row():\n","\n","                message_input = gr.Textbox(\n","                    label=\"Your message\",\n","                    placeholder=\"Write your message here...\",\n","                    lines=4,\n","                    max_lines=10,\n","                    scale=5,\n","                    elem_id=\"message-input\"\n","                )\n","\n","                image_input = gr.Image(\n","                    label=\"Optional image\",\n","                    type=\"pil\",\n","                    height=150,\n","                    sources=[\"upload\", \"clipboard\"],\n","                    scale=2\n","                )\n","\n","            with gr.Row():\n","\n","                send_button = gr.Button(\n","                    \"Send\",\n","                    variant=\"primary\",\n","                    elem_id=\"send-button\",\n","                    scale=3\n","                )\n","\n","                clear_button = gr.Button(\n","                    \"Clear conversation\",\n","                    variant=\"secondary\",\n","                    elem_id=\"clear-button\",\n","                    scale=1\n","                )\n","\n","        with gr.Column(scale=3):\n","\n","            gr.Markdown(\"## Generation settings\")\n","\n","            max_new_tokens = gr.Slider(\n","                minimum=128,\n","                maximum=4096,\n","                value=1024,\n","                step=128,\n","                label=\"Maximum new tokens\"\n","            )\n","\n","            temperature = gr.Slider(\n","                minimum=0.0,\n","                maximum=1.5,\n","                value=0.7,\n","                step=0.05,\n","                label=\"Temperature\"\n","            )\n","\n","            top_p = gr.Slider(\n","                minimum=0.1,\n","                maximum=1.0,\n","                value=0.9,\n","                step=0.05,\n","                label=\"Top-p\"\n","            )\n","\n","            gr.Markdown(\n","                \"\"\"\n","                **Tip:** Set temperature to `0` for deterministic\n","                generation. Increase maximum tokens for longer responses.\n","                \"\"\"\n","            )\n","\n","    gr.Markdown(\"---\")\n","\n","    gr.Markdown(\"## Latest model response\")\n","\n","    with gr.Row():\n","\n","        with gr.Column():\n","\n","            thinking_output = gr.Textbox(\n","                label=\"💭 What the model thinks\",\n","                lines=12,\n","                max_lines=25,\n","                interactive=False,\n","                placeholder=\"Generated thinking will appear here...\",\n","                elem_id=\"thinking-panel\"\n","            )\n","\n","        with gr.Column():\n","\n","            answer_output = gr.Textbox(\n","                label=\"🗣️ What the model says\",\n","                lines=12,\n","                max_lines=25,\n","                interactive=False,\n","                placeholder=\"The final answer will appear here...\",\n","                elem_id=\"answer-panel\"\n","            )\n","\n","    # ========================================================\n","    # EVENTS\n","    # ========================================================\n","\n","    inputs = [\n","        message_input,\n","        image_input,\n","        chatbot,\n","        conversation_state,\n","        max_new_tokens,\n","        temperature,\n","        top_p\n","    ]\n","\n","    outputs = [\n","        chatbot,\n","        conversation_state,\n","        message_input,\n","        image_input,\n","        thinking_output,\n","        answer_output\n","    ]\n","\n","    send_button.click(\n","        fn=chat,\n","        inputs=inputs,\n","        outputs=outputs\n","    )\n","\n","    message_input.submit(\n","        fn=chat,\n","        inputs=inputs,\n","        outputs=outputs\n","    )\n","\n","    clear_button.click(\n","        fn=clear_chat,\n","        inputs=[],\n","        outputs=outputs\n","    )\n","\n","\n","# ============================================================\n","# 14. LAUNCH\n","# ============================================================\n","\n","print(\"\\nStarting Gradio interface...\")\n","\n","demo.queue().launch(\n","    share=True,\n","    debug=True,\n","    show_error=True\n",")\n"]}]}