richarderkhov/mncai_-_agiin-11.1b-v0.0-gguf overview

{
  "metadata": {},
  "card_data": {
    "frontmatter": {},
    "hero_image_url": "",
    "summary": "### Introduction of MindsAndCompany https://mnc.ai/ We create various AI models and develop solutions that can be applied to businesses. And as for generative AI, we are developing products like Code Assistant, TOD Chatbot, LLMOps, and are in the process of developing Enterprise AGI (Artificial General Intelligence). ### Model Summary based mistral arch. pretrain, instruction tuned and dpo. ### How to Use Here give some examples of how to use our model. ``python from transformers import AutoConfig, AutoModel, AutoTokenizer import transformers import torch hf_model = 'mncai/agiin-11.1B-v0.0' message = \"\\n두 개의 구가 있는데 각각 지름이 1, 2일때 각 구의 부피는 몇배야? 설명도 같이 해줘.\\n\\n\" sequences = pipeline( message, do_sample=True, top_k=10, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id, max_length=2048, ) for seq in sequences: print(f\"Result: {seq['generated_text']}\") `` ### Contact If you have any questions, please raise an issue or contact us at dwmyoung@mnc.ai",
    "quick_links": [],
    "benchmark_table_html": "",
    "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\nagiin-11.1B-v0.0 - GGUF\n- Model creator: https://huggingface.co/mncai/\n- Original model: https://huggingface.co/mncai/agiin-11.1B-v0.0/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [agiin-11.1B-v0.0.Q2_K.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q2_K.gguf) | Q2_K | 3.88GB |\n| [agiin-11.1B-v0.0.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.IQ3_XS.gguf) | IQ3_XS | 4.31GB |\n| [agiin-11.1B-v0.0.IQ3_S.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.IQ3_S.gguf) | IQ3_S | 4.54GB |\n| [agiin-11.1B-v0.0.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q3_K_S.gguf) | Q3_K_S | 4.52GB |\n| [agiin-11.1B-v0.0.IQ3_M.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.IQ3_M.gguf) | IQ3_M | 4.69GB |\n| [agiin-11.1B-v0.0.Q3_K.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q3_K.gguf) | Q3_K | 5.03GB |\n| [agiin-11.1B-v0.0.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q3_K_M.gguf) | Q3_K_M | 5.03GB |\n| [agiin-11.1B-v0.0.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q3_K_L.gguf) | Q3_K_L | 5.48GB |\n| [agiin-11.1B-v0.0.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.IQ4_XS.gguf) | IQ4_XS | 5.64GB |\n| [agiin-11.1B-v0.0.Q4_0.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q4_0.gguf) | Q4_0 | 5.88GB |\n| [agiin-11.1B-v0.0.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.IQ4_NL.gguf) | IQ4_NL | 5.95GB |\n| [agiin-11.1B-v0.0.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q4_K_S.gguf) | Q4_K_S | 5.93GB |\n| [agiin-11.1B-v0.0.Q4_K.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q4_K.gguf) | Q4_K | 6.26GB |\n| [agiin-11.1B-v0.0.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q4_K_M.gguf) | Q4_K_M | 6.26GB |\n| [agiin-11.1B-v0.0.Q4_1.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q4_1.gguf) | Q4_1 | 6.53GB |\n| [agiin-11.1B-v0.0.Q5_0.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q5_0.gguf) | Q5_0 | 7.17GB |\n| [agiin-11.1B-v0.0.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q5_K_S.gguf) | Q5_K_S | 7.17GB |\n| [agiin-11.1B-v0.0.Q5_K.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q5_K.gguf) | Q5_K | 7.36GB |\n| [agiin-11.1B-v0.0.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q5_K_M.gguf) | Q5_K_M | 7.36GB |\n| [agiin-11.1B-v0.0.Q5_1.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q5_1.gguf) | Q5_1 | 7.81GB |\n| [agiin-11.1B-v0.0.Q6_K.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q6_K.gguf) | Q6_K | 8.53GB |\n| [agiin-11.1B-v0.0.Q8_0.gguf](https://huggingface.co/RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf/blob/main/agiin-11.1B-v0.0.Q8_0.gguf) | Q8_0 | 11.05GB |\n\n\n\n\nOriginal model description:\n---\nlicense: apache-2.0\nlanguage:\n- en\n---\n# Model Card for mncai/agiin-11.1B-v0.0\n\n### Introduction of MindsAndCompany\n\nhttps://mnc.ai/\n\nWe create various AI models and develop solutions that can be applied to businesses. And as for generative AI, we are developing products like Code Assistant, TOD Chatbot, LLMOps, and are in the process of developing Enterprise AGI (Artificial General Intelligence).\n\n### Model Summary\nbased mistral arch. pretrain, instruction tuned and dpo.\n\n\n### How to Use\nHere give some examples of how to use our model.\n\n```python\nfrom transformers import AutoConfig, AutoModel, AutoTokenizer\nimport transformers\nimport torch\nhf_model = 'mncai/agiin-11.1B-v0.0' \nmessage = \"<|user|>\\n두 개의 구가 있는데 각각 지름이 1, 2일때 각 구의 부피는 몇배야? 설명도 같이 해줘.\\n<|assistant|>\\n\"\n\nsequences = pipeline(\n    message,\n    do_sample=True,\n    top_k=10,\n    num_return_sequences=1,\n    eos_token_id=tokenizer.eos_token_id,\n    max_length=2048,\n)\nfor seq in sequences:\n    print(f\"Result: {seq['generated_text']}\")\n```\n\n\n### Contact\nIf you have any questions, please raise an issue or contact us at dwmyoung@mnc.ai\n\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 96,
  "gated": false,
  "private": false,
  "last_modified": "2024-07-02T16:20:54.000Z",
  "created_at": "2024-07-02T11:39:12.000Z",
  "pipeline_tag": "",
  "library_name": ""
}

{
  "_id": "6683e6e0a4ebc8d956feaff2",
  "id": "RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf",
  "modelId": "RichardErkhov/mncai_-_agiin-11.1B-v0.0-gguf",
  "sha": "aa98e78971c7420e2b53d242562275b2ad9f82fe",
  "createdAt": "2024-07-02T11:39:12.000Z",
  "lastModified": "2024-07-02T16:20:54.000Z",
  "author": "RichardErkhov",
  "downloads": 96,
  "likes": 0,
  "gated": false,
  "private": false,
  "pipeline_tag": "",
  "library_name": "",
  "siblings_count": 24
}