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richarderkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf overview

Summary This model was trained using H2O LLM Studio. Visit H2O LLM Studio to learn how to train your own large language models.

ggufendpoints_compatibleregion:usconversational
richarderkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf visual
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87
Likes
0
Pipeline
Library
Visibility
Public
Access
Open

Repository Files & Downloads

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Direct downloads for all repository files
FileTypeQuantizationSizeLink
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_M.gguf GGUF IQ3_M 3.06 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_S.gguf GGUF IQ3_S 2.96 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_XS.gguf GGUF IQ3_XS 2.81 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ4_NL.gguf GGUF IQ4_NL 3.87 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ4_XS.gguf GGUF IQ4_XS 3.67 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q2_K.gguf GGUF Q2_K 2.53 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K.gguf GGUF Q3_K 3.28 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_L.gguf GGUF Q3_K_L 3.56 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_M.gguf GGUF Q3_K_M 3.28 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_S.gguf GGUF Q3_K_S 2.95 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_0.gguf GGUF 3.83 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_1.gguf GGUF 4.24 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K.gguf GGUF Q4_K 4.07 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K_M.gguf GGUF Q4_K_M 4.07 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K_S.gguf GGUF Q4_K_S 3.86 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_0.gguf GGUF 4.65 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_1.gguf GGUF 5.07 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K.gguf GGUF Q5_K 4.78 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K_M.gguf GGUF Q5_K_M 4.78 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K_S.gguf GGUF Q5_K_S 4.65 GB Download
h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q6_K.gguf GGUF Q6_K 5.53 GB Download

Model Details Live

Model Slug
richarderkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf
Author
RichardErkhov
Pipeline Task
Library
Created
2024-05-11
Last Modified
2024-05-11
Gated
No
Private
No
HF SHA
a47a3e9f5cec16ff022d914a616ac39ccf19800f
License
Unknown
Language
Unknown
Base Model
Unknown

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "frontmatter": {},
    "hero_image_url": "",
    "summary": "## Summary This model was trained using H2O LLM Studio. Visit H2O LLM Studio to learn how to train your own large language models.",
    "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\nh2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1 - GGUF\n- Model creator: https://huggingface.co/h2oai/\n- Original model: https://huggingface.co/h2oai/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q2_K.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q2_K.gguf) | Q2_K | 2.53GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_XS.gguf) | IQ3_XS | 2.81GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_S.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_S.gguf) | IQ3_S | 2.96GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_S.gguf) | Q3_K_S | 2.95GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_M.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ3_M.gguf) | IQ3_M | 3.06GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K.gguf) | Q3_K | 3.28GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_M.gguf) | Q3_K_M | 3.28GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q3_K_L.gguf) | Q3_K_L | 3.56GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ4_XS.gguf) | IQ4_XS | 3.67GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_0.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_0.gguf) | Q4_0 | 3.83GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.IQ4_NL.gguf) | IQ4_NL | 3.87GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K_S.gguf) | Q4_K_S | 3.86GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K.gguf) | Q4_K | 4.07GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_K_M.gguf) | Q4_K_M | 4.07GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_1.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q4_1.gguf) | Q4_1 | 4.24GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_0.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_0.gguf) | Q5_0 | 4.65GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K_S.gguf) | Q5_K_S | 4.65GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K.gguf) | Q5_K | 4.78GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_K_M.gguf) | Q5_K_M | 4.78GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_1.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q5_1.gguf) | Q5_1 | 5.07GB |\n| [h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q6_K.gguf](https://huggingface.co/RichardErkhov/h2oai_-_h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1-gguf/blob/main/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1.Q6_K.gguf) | Q6_K | 5.53GB |\n\n\n\n\nOriginal model description:\n---\nlanguage:\n- en\nlibrary_name: transformers\ntags:\n- gpt\n- llm\n- large language model\n- h2o-llmstudio\ninference: false\nthumbnail: >-\n  https://h2o.ai/etc.clientlibs/h2o/clientlibs/clientlib-site/resources/images/favicon.ico\nlicense: apache-2.0\n---\n# Model Card\n## Summary\n\nThis model was trained using [H2O LLM Studio](https://github.com/h2oai/h2o-llmstudio). Visit [H2O LLM Studio](https://github.com/h2oai/h2o-llmstudio) to learn how to train your own large language models.\n- Base model: [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)\n\n## Usage\n\nTo use the model with the `transformers` library on a machine with GPUs, first make sure you have the `transformers` library installed.\n\n```bash\npip install transformers==4.36.1\n```\n\n```python\nimport torch\nfrom transformers import pipeline\n\npipe = pipeline(\n    \"text-generation\",\n    model=\"h2oai/h2ogpt-gm-7b-mistral-chat-sft-dpo-rag-v1\",\n    torch_dtype=torch.bfloat16,\n    device_map=\"auto\",\n)\n\n# We use the HF Tokenizer chat template to format each message\n# https://huggingface.co/docs/transformers/main/en/chat_templating\nmessages = [\n    {\"role\": \"user\", \"content\": \"Why is drinking water so healthy?\"},\n]\nprompt = pipe.tokenizer.apply_chat_template(\n    messages,\n    tokenize=False,\n    add_generation_prompt=True,\n)\nres = pipe(\n    prompt,\n    max_new_tokens=256,\n)\nprint(res[0][\"generated_text\"])\n# <|system|>You are a friendly chatbot</s><|prompt|>Why is drinking water so healthy?</s><|answer|> Drinking water is healthy for several reasons: [...]\n```\n\n## Quantization and sharding\n\nYou can load the models using quantization by specifying ```load_in_8bit=True``` or ```load_in_4bit=True```. Also, sharding on multiple GPUs is possible by setting ```device_map=auto```.\n\n## Model Architecture\n\n```\nMistralForCausalLM(\n  (model): MistralModel(\n    (embed_tokens): Embedding(32000, 4096, padding_idx=0)\n    (layers): ModuleList(\n      (0-31): 32 x MistralDecoderLayer(\n        (self_attn): MistralAttention(\n          (q_proj): Linear(in_features=4096, out_features=4096, bias=False)\n          (k_proj): Linear(in_features=4096, out_features=1024, bias=False)\n          (v_proj): Linear(in_features=4096, out_features=1024, bias=False)\n          (o_proj): Linear(in_features=4096, out_features=4096, bias=False)\n          (rotary_emb): MistralRotaryEmbedding()\n        )\n        (mlp): MistralMLP(\n          (gate_proj): Linear(in_features=4096, out_features=14336, bias=False)\n          (up_proj): Linear(in_features=4096, out_features=14336, bias=False)\n          (down_proj): Linear(in_features=14336, out_features=4096, bias=False)\n          (act_fn): SiLUActivation()\n        )\n        (input_layernorm): MistralRMSNorm()\n        (post_attention_layernorm): MistralRMSNorm()\n      )\n    )\n    (norm): MistralRMSNorm()\n  )\n  (lm_head): Linear(in_features=4096, out_features=32000, bias=False)\n)\n```\n\n## Disclaimer\n\nPlease read this disclaimer carefully before using the large language model provided in this repository. Your use of the model signifies your agreement to the following terms and conditions.\n\n- Biases and Offensiveness: The large language model is trained on a diverse range of internet text data, which may contain biased, racist, offensive, or otherwise inappropriate content. By using this model, you acknowledge and accept that the generated content may sometimes exhibit biases or produce content that is offensive or inappropriate. The developers of this repository do not endorse, support, or promote any such content or viewpoints.\n- Limitations: The large language model is an AI-based tool and not a human. It may produce incorrect, nonsensical, or irrelevant responses. It is the user's responsibility to critically evaluate the generated content and use it at their discretion.\n- Use at Your Own Risk: Users of this large language model must assume full responsibility for any consequences that may arise from their use of the tool. The developers and contributors of this repository shall not be held liable for any damages, losses, or harm resulting from the use or misuse of the provided model.\n- Ethical Considerations: Users are encouraged to use the large language model responsibly and ethically. By using this model, you agree not to use it for purposes that promote hate speech, discrimination, harassment, or any form of illegal or harmful activities.\n- Reporting Issues: If you encounter any biased, offensive, or otherwise inappropriate content generated by the large language model, please report it to the repository maintainers through the provided channels. Your feedback will help improve the model and mitigate potential issues.\n- Changes to this Disclaimer: The developers of this repository reserve the right to modify or update this disclaimer at any time without prior notice. It is the user's responsibility to periodically review the disclaimer to stay informed about any changes.\n\nBy using the large language model provided in this repository, you agree to accept and comply with the terms and conditions outlined in this disclaimer. If you do not agree with any part of this disclaimer, you should refrain from using the model and any content generated by it.\n\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 87,
  "gated": false,
  "private": false,
  "last_modified": "2024-05-11T06:54:29.000Z",
  "created_at": "2024-05-11T04:59:26.000Z",
  "pipeline_tag": "",
  "library_name": ""
}
Source payload excerpt (from Hugging Face API)
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