Delete Hellsing/build joycap sdnq.ipynb

Hellsing/build joycap sdnq.ipynb

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-{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[{"file_id":"1Twu47NmzZePVabgczjU-vw9pSp_MUJ6V","timestamp":1777053207201}],"collapsed_sections":["VdKv9Jahjsbd"],"gpuType":"T4","authorship_tag":"ABX9TyNEJSCJB+iOHQTjJxdM78h9"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","source":["# New"],"metadata":{"id":"c0yCIbvJnRAL"}},{"cell_type":"code","source":["#@markdown ## 1 - Setup environment (clean install)\n","\n","from google.colab import drive, userdata\n","\n","drive.mount('/content/drive')\n","\n","hf_token = userdata.get(\"HF_TOKEN\")\n","\n","if hf_token:\n","    from huggingface_hub import login\n","    login(token=hf_token)\n","\n","print(\"✅ Drive + HF login ready\")"],"metadata":{"cellView":"form","id":"58JPv1RKnUoz"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#@markdown ## 2 - Install correct dependencies (FIXED VERSIONS)\n","\n","!pip uninstall -y transformers tokenizers -q\n","\n","!pip install -q \\\n","    transformers==4.41.2 \\\n","    tokenizers==0.19.1 \\\n","    accelerate \\\n","    huggingface_hub \\\n","    safetensors \\\n","    sdnq\n","\n","print(\"✅ Dependencies installed\")"],"metadata":{"cellView":"form","id":"G9162XsznXiN"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#@markdown ## 4 - Load model + processor\n","\n","import torch\n","from transformers import AutoProcessor, AutoModelForVision2Seq\n","\n","repo_id = \"fancyfeast/llama-joycaption-beta-one-hf-llava\"\n","\n","print(\"⏳ Loading processor...\")\n","processor = AutoProcessor.from_pretrained(\n","    repo_id,\n","    trust_remote_code=True\n",")\n","\n","print(\"⏳ Loading model...\")\n","model = AutoModelForVision2Seq.from_pretrained(\n","    repo_id,\n","    torch_dtype=torch.float16,\n","    device_map=\"cpu\",\n","    low_cpu_mem_usage=True,\n","    trust_remote_code=True\n",")\n","\n","print(\"✅ Model loaded\")"],"metadata":{"cellView":"form","id":"35U_kIn4nl9A"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#@markdown ## 5 - Pipeline wrapper\n","\n","class JoyCaptionPipe:\n","    def __init__(self, model, processor):\n","        self.model = model\n","        self.processor = processor\n","        self.device = torch.device(\"cpu\")\n","\n","    def __call__(self, image, prompt=\"Describe this image\"):\n","        inputs = self.processor(\n","            text=prompt,\n","            images=image,\n","            return_tensors=\"pt\"\n","        )\n","\n","        with torch.no_grad():\n","            output = self.model.generate(\n","                **inputs,\n","                max_new_tokens=128\n","            )\n","\n","        return self.processor.batch_decode(\n","            output,\n","            skip_special_tokens=True\n","        )[0]\n","\n","\n","pipe = JoyCaptionPipe(model, processor)\n","\n","print(\"✅ Pipeline ready\")"],"metadata":{"cellView":"form","id":"icfmFpUCnpvE"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#@markdown ## 6 - SDNQ Configuration (CPU FIXED)\n","\n","from sdnq import SDNQConfig, sdnq_post_load_quant\n","import gc\n","\n","sdnq_config = SDNQConfig(\n","    weights_dtype=\"uin4\",\n","    quantized_matmul_dtype=\"int8\",\n","    group_size=0,\n","    svd_rank=32,\n","    svd_steps=8,\n","    use_svd=False,\n","    quant_conv=False,\n","    quant_embedding=False,\n","    use_quantized_matmul=True,\n","    use_dynamic_quantization=True,\n","    dequantize_fp32=True,\n","    non_blocking=False,\n","    add_skip_keys=True,\n","\n","    # ✅ FIXED (was CUDA → now CPU)\n","    quantization_device=\"cpu\",\n","    return_device=\"cpu\",\n","\n","    modules_to_not_convert=[\n","        \"correction_coefs\",\n","        \"prediction_coefs\",\n","        \"lm_head\",\n","        \"embedding_projection\"\n","    ],\n","\n","    modules_dtype_dict={\"int8\": [\"lm_head\"]},\n","\n","    modules_quant_config={\n","        \"embed_tokens_per_layer\": {\n","            \"quantization_device\": \"cpu\"\n","        }\n","    },\n",")\n","\n","print(\"⏳ Applying SDNQ quantization...\")\n","\n","pipe.model = sdnq_post_load_quant(\n","    pipe.model,\n","    **sdnq_config.__dict__\n",")\n","\n","gc.collect()\n","\n","print(\"✅ SDNQ quantization complete\")"],"metadata":{"id":"57D6k_NJnu78"},"execution_count":null,"outputs":[]}]}