richarderkhov/inneri_-_innerillm-0x00d0-7b-slerp-gguf overview

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    "summary": "InnerILLM-0x00d0-Ox0dad0-Nous-Yarn-Mistral-7B-slerp is a merge of the following models using LazyMergekit: * NousResearch/Yarn-Mistral-7b-128k * InnerI/InnerILLM-0x00d0-Ox0dad0-nous-nous-v2.0-7B-slerp",
    "quick_links": [],
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    "readme_markdown": "Quantization made by Richard Erkhov.\n\n[Github](https://github.com/RichardErkhov)\n\n[Discord](https://discord.gg/pvy7H8DZMG)\n\n[Request more models](https://github.com/RichardErkhov/quant_request)\n\n\nInnerILLM-0x00d0-7B-slerp - GGUF\n- Model creator: https://huggingface.co/InnerI/\n- Original model: https://huggingface.co/InnerI/InnerILLM-0x00d0-7B-slerp/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [InnerILLM-0x00d0-7B-slerp.Q2_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q2_K.gguf) | Q2_K | 2.53GB |\n| [InnerILLM-0x00d0-7B-slerp.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.IQ3_XS.gguf) | IQ3_XS | 2.81GB |\n| [InnerILLM-0x00d0-7B-slerp.IQ3_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.IQ3_S.gguf) | IQ3_S | 2.96GB |\n| [InnerILLM-0x00d0-7B-slerp.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q3_K_S.gguf) | Q3_K_S | 2.95GB |\n| [InnerILLM-0x00d0-7B-slerp.IQ3_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.IQ3_M.gguf) | IQ3_M | 3.06GB |\n| [InnerILLM-0x00d0-7B-slerp.Q3_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q3_K.gguf) | Q3_K | 3.28GB |\n| [InnerILLM-0x00d0-7B-slerp.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q3_K_M.gguf) | Q3_K_M | 3.28GB |\n| [InnerILLM-0x00d0-7B-slerp.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q3_K_L.gguf) | Q3_K_L | 3.56GB |\n| [InnerILLM-0x00d0-7B-slerp.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.IQ4_XS.gguf) | IQ4_XS | 3.67GB |\n| [InnerILLM-0x00d0-7B-slerp.Q4_0.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q4_0.gguf) | Q4_0 | 3.83GB |\n| [InnerILLM-0x00d0-7B-slerp.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.IQ4_NL.gguf) | IQ4_NL | 3.87GB |\n| [InnerILLM-0x00d0-7B-slerp.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q4_K_S.gguf) | Q4_K_S | 3.86GB |\n| [InnerILLM-0x00d0-7B-slerp.Q4_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q4_K.gguf) | Q4_K | 4.07GB |\n| [InnerILLM-0x00d0-7B-slerp.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q4_K_M.gguf) | Q4_K_M | 4.07GB |\n| [InnerILLM-0x00d0-7B-slerp.Q4_1.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q4_1.gguf) | Q4_1 | 4.24GB |\n| [InnerILLM-0x00d0-7B-slerp.Q5_0.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q5_0.gguf) | Q5_0 | 4.65GB |\n| [InnerILLM-0x00d0-7B-slerp.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q5_K_S.gguf) | Q5_K_S | 4.65GB |\n| [InnerILLM-0x00d0-7B-slerp.Q5_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q5_K.gguf) | Q5_K | 4.78GB |\n| [InnerILLM-0x00d0-7B-slerp.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q5_K_M.gguf) | Q5_K_M | 4.78GB |\n| [InnerILLM-0x00d0-7B-slerp.Q5_1.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q5_1.gguf) | Q5_1 | 5.07GB |\n| [InnerILLM-0x00d0-7B-slerp.Q6_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q6_K.gguf) | Q6_K | 5.53GB |\n| [InnerILLM-0x00d0-7B-slerp.Q8_0.gguf](https://huggingface.co/RichardErkhov/InnerI_-_InnerILLM-0x00d0-7B-slerp-gguf/blob/main/InnerILLM-0x00d0-7B-slerp.Q8_0.gguf) | Q8_0 | 7.17GB |\n\n\n\n\nOriginal model description:\n---\ntags:\n- merge\n- mergekit\n- lazymergekit\n- NousResearch/Yarn-Mistral-7b-128k\n- InnerI/InnerILLM-0x00d0-Ox0dad0-nous-nous-v2.0-7B-slerp\nbase_model:\n- NousResearch/Yarn-Mistral-7b-128k\n- InnerI/InnerILLM-0x00d0-Ox0dad0-nous-nous-v2.0-7B-slerp\nlicense: apache-2.0\n---\n\n# InnerILLM-0x00d0-Ox0dad0-Nous-Yarn-Mistral-7B-slerp\n\nInnerILLM-0x00d0-Ox0dad0-Nous-Yarn-Mistral-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):\n* [NousResearch/Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k)\n* [InnerI/InnerILLM-0x00d0-Ox0dad0-nous-nous-v2.0-7B-slerp](https://huggingface.co/InnerI/InnerILLM-0x00d0-Ox0dad0-nous-nous-v2.0-7B-slerp)\n\n## 🧩 Configuration\n\n```yaml\nslices:\n  - sources:\n      - model: NousResearch/Yarn-Mistral-7b-128k\n        layer_range: [0, 32]\n      - model: InnerI/InnerILLM-0x00d0-Ox0dad0-nous-nous-v2.0-7B-slerp\n        layer_range: [0, 32]\nmerge_method: slerp\nbase_model: NousResearch/Yarn-Mistral-7b-128k\nparameters:\n  t:\n    - filter: self_attn\n      value: [0, 0.5, 0.3, 0.7, 1]\n    - filter: mlp\n      value: [1, 0.5, 0.7, 0.3, 0]\n    - value: 0.5\ndtype: bfloat16\n```\n\n## 💻 Usage\n\n```python\n!pip install -qU transformers accelerate\n\nfrom transformers import AutoTokenizer\nimport transformers\nimport torch\n\nmodel = \"InnerI/InnerILLM-0x00d0-Ox0dad0-Nous-Yarn-Mistral-7B-slerp\"\nmessages = [{\"role\": \"user\", \"content\": \"What is a large language model?\"}]\n\ntokenizer = AutoTokenizer.from_pretrained(model)\nprompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\npipeline = transformers.pipeline(\n    \"text-generation\",\n    model=model,\n    torch_dtype=torch.float16,\n    device_map=\"auto\",\n)\n\noutputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)\nprint(outputs[0][\"generated_text\"])\n```\n\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "endpoints_compatible",
    "region:us"
  ],
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  "last_modified": "2024-09-05T23:14:50.000Z",
  "created_at": "2024-09-05T16:14:33.000Z",
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