mylesgoose/llama-3.2-1b-instruct-abliterated2-q8_0-gguf overview

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    "base_model": "mylesgoose/Llama-3.2-1B-Instruct-abliterated2",
    "library_name": "transformers",
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    "frontmatter": {
      "base_model": "mylesgoose/Llama-3.2-1B-Instruct-abliterated2",
      "library_name": "transformers",
      "tags": [
        "llama-cpp",
        "gguf-my-repo"
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    "summary": "This model was converted to GGUF format from mylesgoose/Llama-3.2-1B-Instruct-abliterated2 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.",
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    "readme_markdown": "---\nbase_model: mylesgoose/Llama-3.2-1B-Instruct-abliterated2\nlibrary_name: transformers\ntags:\n- llama-cpp\n- gguf-my-repo\n---\n\n# mylesgoose/Llama-3.2-1B-Instruct-abliterated2-Q8_0-GGUF\nThis model was converted to GGUF format from [`mylesgoose/Llama-3.2-1B-Instruct-abliterated2`](https://huggingface.co/mylesgoose/Llama-3.2-1B-Instruct-abliterated2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.\nRefer to the [original model card](https://huggingface.co/mylesgoose/Llama-3.2-1B-Instruct-abliterated2) for more details on the model.\n\n## Use with llama.cpp\nInstall llama.cpp through brew (works on Mac and Linux)\n\n```bash\nbrew install llama.cpp\n\n```\nInvoke the llama.cpp server or the CLI.\n\n### CLI:\n```bash\nllama-cli --hf-repo mylesgoose/Llama-3.2-1B-Instruct-abliterated2-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated2-q8_0.gguf -p \"The meaning to life and the universe is\"\n```\n\n### Server:\n```bash\nllama-server --hf-repo mylesgoose/Llama-3.2-1B-Instruct-abliterated2-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated2-q8_0.gguf -c 2048\n```\n\nNote: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.\n\nStep 1: Clone llama.cpp from GitHub.\n```\ngit clone https://github.com/ggerganov/llama.cpp\n```\n\nStep 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).\n```\ncd llama.cpp && LLAMA_CURL=1 make\n```\n\nStep 3: Run inference through the main binary.\n```\n./llama-cli --hf-repo mylesgoose/Llama-3.2-1B-Instruct-abliterated2-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated2-q8_0.gguf -p \"The meaning to life and the universe is\"\n```\nor \n```\n./llama-server --hf-repo mylesgoose/Llama-3.2-1B-Instruct-abliterated2-Q8_0-GGUF --hf-file llama-3.2-1b-instruct-abliterated2-q8_0.gguf -c 2048\n```\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "llama-cpp",
    "gguf-my-repo",
    "base_model:mylesgoose/Llama-3.2-1B-Instruct-abliterated2",
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  "last_modified": "2024-10-01T01:39:51.000Z",
  "created_at": "2024-10-01T01:39:43.000Z",
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  "library_name": "transformers"
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