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devingulliver/mamba-gguf Q2_K GGUF - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.

Model Intelligence Sheet

devingulliver/mamba-gguf overview

These are the Mamba base models, converted to GGUF for use with llama.cpp, in a variety of precisions (2, 3, 4, 5, 6, 8, 16, and 32-bit). Please click "Files and versions" at the top of the page to choose your desired model size, and then click the "๐Ÿ“ฆLFS โ†“" button next to your desired quantization. Here is a table adapted from TheBloke explaining the various precisions: | Quant method | Use case | | ---- | ---- | | Q2K | significant quality loss - not recommended for most purposes | | Q3KS | very small, high quality loss | | Q3KM | very small, high quality loss | | Q3KL | small, substantial quality loss | | Q40 | legacy; small, very high quality loss - prefer using Q3KM | | Q4KS | small, greater quality loss | | Q4KM | medium, balanced quality - recommended | | Q50 | legacy; medium, balanced quality - prefer using Q4KM | | Q5KS | large, low quality loss - recommended | | Q5KM | large, very low quality loss - recommended | | Q6K | very large, extremely low quality loss | | Q8_0 | very large, extremely low quality loss - not recommended | | F16 | half precision - almost identical to the original | | F32 | original precision - recommended by the Mamba authors |

ggufmergetext-generationbase_model:state-spaces/mamba-1.4bbase_model:merge:state-spaces/mamba-1.4bbase_model:state-spaces/mamba-130mbase_model:merge:state-spaces/mamba-130mbase_model:state-spaces/mamba-2.8bbase_model:merge:state-spaces/mamba-2.8bbase_model:state-spaces/mamba-2.8b-slimpjbase_model:merge:state-spaces/mamba-2.8b-slimpjbase_model:state-spaces/mamba-370mbase_model:merge:state-spaces/mamba-370mbase_model:state-spaces/mamba-790mbase_model:merge:state-spaces/mamba-790mlicense:apache-2.0endpoints_compatibleregion:us
devingulliver/mamba-gguf visual
Downloads
258
Likes
2
Pipeline
text-generation
Library
โ€”
Visibility
Public
Access
Open

Repository Files & Downloads

84 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
mamba-1.4b-f16.gguf GGUF F16 2.67 GB Download
mamba-1.4b-f32.gguf GGUF F32 5.11 GB Download
mamba-1.4b-q2_k.gguf GGUF Q2_K 693.90 MB Download
mamba-1.4b-q3_k_l.gguf GGUF Q3_K_L 810.90 MB Download
mamba-1.4b-q3_k_m.gguf GGUF Q3_K_M 810.90 MB Download
mamba-1.4b-q3_k_s.gguf GGUF Q3_K_S 810.90 MB Download
mamba-1.4b-q4_0.gguf GGUF โ€” 963.90 MB Download
mamba-1.4b-q4_k_m.gguf GGUF Q4_K_M 963.90 MB Download
mamba-1.4b-q4_k_s.gguf GGUF Q4_K_S 963.90 MB Download
mamba-1.4b-q5_0.gguf GGUF โ€” 1.08 GB Download
mamba-1.4b-q5_k_m.gguf GGUF Q5_K_M 1.08 GB Download
mamba-1.4b-q5_k_s.gguf GGUF Q5_K_S 1.08 GB Download
mamba-1.4b-q6_k.gguf GGUF Q6_K 1.23 GB Download
mamba-1.4b-q8_0.gguf GGUF โ€” 1.53 GB Download
mamba-130m-f16.gguf GGUF F16 258.66 MB Download
mamba-130m-f32.gguf GGUF F32 494.31 MB Download
mamba-130m-q2_k.gguf GGUF Q2_K 79.79 MB Download
mamba-130m-q3_k_l.gguf GGUF Q3_K_L 88.02 MB Download
mamba-130m-q3_k_m.gguf GGUF Q3_K_M 88.02 MB Download
mamba-130m-q3_k_s.gguf GGUF Q3_K_S 88.02 MB Download
mamba-130m-q4_0.gguf GGUF โ€” 98.78 MB Download
mamba-130m-q4_k_m.gguf GGUF Q4_K_M 98.78 MB Download
mamba-130m-q4_k_s.gguf GGUF Q4_K_S 98.78 MB Download
mamba-130m-q5_0.gguf GGUF โ€” 108.90 MB Download
mamba-130m-q5_k_m.gguf GGUF Q5_K_M 108.90 MB Download
mamba-130m-q5_k_s.gguf GGUF Q5_K_S 108.90 MB Download
mamba-130m-q6_k.gguf GGUF Q6_K 119.66 MB Download
mamba-130m-q8_0.gguf GGUF โ€” 148.20 MB Download
mamba-2.8b-f16.gguf GGUF F16 Unknown Download
mamba-2.8b-f32.gguf GGUF F32 Unknown Download
mamba-2.8b-q2_k.gguf GGUF Q2_K Unknown Download
mamba-2.8b-q3_k_l.gguf GGUF Q3_K_L Unknown Download
mamba-2.8b-q3_k_m.gguf GGUF Q3_K_M Unknown Download
mamba-2.8b-q3_k_s.gguf GGUF Q3_K_S Unknown Download
mamba-2.8b-q4_0.gguf GGUF โ€” Unknown Download
mamba-2.8b-q4_k_m.gguf GGUF Q4_K_M Unknown Download
mamba-2.8b-q4_k_s.gguf GGUF Q4_K_S Unknown Download
mamba-2.8b-q5_0.gguf GGUF โ€” Unknown Download
mamba-2.8b-q5_k_m.gguf GGUF Q5_K_M Unknown Download
mamba-2.8b-q5_k_s.gguf GGUF Q5_K_S Unknown Download
mamba-2.8b-q6_k.gguf GGUF Q6_K Unknown Download
mamba-2.8b-q8_0.gguf GGUF โ€” Unknown Download
mamba-2.8b-slimpj-f16.gguf GGUF F16 5.39 GB Download
mamba-2.8b-slimpj-f32.gguf GGUF F32 10.31 GB Download
mamba-2.8b-slimpj-q2_k.gguf GGUF Q2_K 1.33 GB Download
mamba-2.8b-slimpj-q3_k_l.gguf GGUF Q3_K_L 1.57 GB Download
mamba-2.8b-slimpj-q3_k_m.gguf GGUF Q3_K_M 1.57 GB Download
mamba-2.8b-slimpj-q3_k_s.gguf GGUF Q3_K_S 1.57 GB Download
mamba-2.8b-slimpj-q4_0.gguf GGUF โ€” 1.88 GB Download
mamba-2.8b-slimpj-q4_k_m.gguf GGUF Q4_K_M 1.88 GB Download
mamba-2.8b-slimpj-q4_k_s.gguf GGUF Q4_K_S 1.88 GB Download
mamba-2.8b-slimpj-q5_0.gguf GGUF โ€” 2.17 GB Download
mamba-2.8b-slimpj-q5_k_m.gguf GGUF Q5_K_M 2.17 GB Download
mamba-2.8b-slimpj-q5_k_s.gguf GGUF Q5_K_S 2.17 GB Download
mamba-2.8b-slimpj-q6_k.gguf GGUF Q6_K 2.48 GB Download
mamba-2.8b-slimpj-q8_0.gguf GGUF โ€” 3.08 GB Download
mamba-370m-f16.gguf GGUF F16 Unknown Download
mamba-370m-f32.gguf GGUF F32 Unknown Download
mamba-370m-q2_k.gguf GGUF Q2_K Unknown Download
mamba-370m-q3_k_l.gguf GGUF Q3_K_L Unknown Download
mamba-370m-q3_k_m.gguf GGUF Q3_K_M Unknown Download
mamba-370m-q3_k_s.gguf GGUF Q3_K_S Unknown Download
mamba-370m-q4_0.gguf GGUF โ€” Unknown Download
mamba-370m-q4_k_m.gguf GGUF Q4_K_M Unknown Download
mamba-370m-q4_k_s.gguf GGUF Q4_K_S Unknown Download
mamba-370m-q5_0.gguf GGUF โ€” Unknown Download
mamba-370m-q5_k_m.gguf GGUF Q5_K_M Unknown Download
mamba-370m-q5_k_s.gguf GGUF Q5_K_S Unknown Download
mamba-370m-q6_k.gguf GGUF Q6_K Unknown Download
mamba-370m-q8_0.gguf GGUF โ€” Unknown Download
mamba-790m-f16.gguf GGUF F16 Unknown Download
mamba-790m-f32.gguf GGUF F32 Unknown Download
mamba-790m-q2_k.gguf GGUF Q2_K Unknown Download
mamba-790m-q3_k_l.gguf GGUF Q3_K_L Unknown Download
mamba-790m-q3_k_m.gguf GGUF Q3_K_M Unknown Download
mamba-790m-q3_k_s.gguf GGUF Q3_K_S Unknown Download
mamba-790m-q4_0.gguf GGUF โ€” Unknown Download
mamba-790m-q4_k_m.gguf GGUF Q4_K_M Unknown Download
mamba-790m-q4_k_s.gguf GGUF Q4_K_S Unknown Download
mamba-790m-q5_0.gguf GGUF โ€” Unknown Download
mamba-790m-q5_k_m.gguf GGUF Q5_K_M Unknown Download
mamba-790m-q5_k_s.gguf GGUF Q5_K_S Unknown Download
mamba-790m-q6_k.gguf GGUF Q6_K Unknown Download
mamba-790m-q8_0.gguf GGUF โ€” Unknown Download

Model Details Live

Model Slug
devingulliver/mamba-gguf
Author
devingulliver
Pipeline Task
text-generation
Library
โ€”
Created
2024-03-12
Last Modified
2024-03-12
Gated
No
Private
No
HF SHA
4f5fc95be23f5aefa5dd1ccd639eabe35c47193b
License
apache-2.0
Language
Unknown
Base Model
state-spaces/mamba-130m, state-spaces/mamba-370m, state-spaces/mamba-790m, state-spaces/mamba-1.4b, state-spaces/mamba-2.8b, state-spaces/mamba-2.8b-slimpj

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "license": "apache-2.0",
    "pipeline_tag": "text-generation",
    "tags": [
      "merge"
    ],
    "base_model": [
      "state-spaces/mamba-130m",
      "state-spaces/mamba-370m",
      "state-spaces/mamba-790m",
      "state-spaces/mamba-1.4b",
      "state-spaces/mamba-2.8b",
      "state-spaces/mamba-2.8b-slimpj"
    ],
    "frontmatter": {
      "license": "apache-2.0",
      "pipeline_tag": "text-generation",
      "tags": [
        "merge"
      ],
      "base_model": [
        "state-spaces/mamba-130m",
        "state-spaces/mamba-370m",
        "state-spaces/mamba-790m",
        "state-spaces/mamba-1.4b",
        "state-spaces/mamba-2.8b",
        "state-spaces/mamba-2.8b-slimpj"
      ]
    },
    "hero_image_url": "",
    "summary": "These are the Mamba base models, converted to GGUF for use with llama.cpp, in a variety of precisions (2, 3, 4, 5, 6, 8, 16, and 32-bit). Please click \"Files and versions\" at the top of the page to choose your desired model size, and then click the \"๐Ÿ“ฆLFS      โ†“\" button next to your desired quantization. Here is a table adapted from TheBloke explaining the various precisions: | Quant method | Use case | | ---- | ---- | | Q2_K | significant quality loss - not recommended for most purposes | | Q3_K_S | very small, high quality loss | | Q3_K_M | very small, high quality loss | | Q3_K_L | small, substantial quality loss | | Q4_0 | legacy; small, very high quality loss - prefer using Q3_K_M | | Q4_K_S | small, greater quality loss | | Q4_K_M | medium, balanced quality - recommended | | Q5_0 | legacy; medium, balanced quality - prefer using Q4_K_M | | Q5_K_S | large, low quality loss - recommended | | Q5_K_M | large, very low quality loss - recommended | | Q6_K | very large, extremely low quality loss | | Q8_0 | very large, extremely low quality loss - not recommended | | F16 | half precision - almost identical to the original | | F32 | original precision - recommended by the Mamba authors |",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nlicense: apache-2.0\npipeline_tag: text-generation\ntags:\n- merge\nbase_model:\n- state-spaces/mamba-130m\n- state-spaces/mamba-370m\n- state-spaces/mamba-790m\n- state-spaces/mamba-1.4b\n- state-spaces/mamba-2.8b\n- state-spaces/mamba-2.8b-slimpj\n---\n\n# Mamba GGUF\n\nThese are the Mamba base models, converted to GGUF for use with [llama.cpp](https://github.com/ggerganov/llama.cpp), in a variety of precisions (2, 3, 4, 5, 6, 8, 16, and 32-bit).\n\nPlease click \"Files and versions\" at the top of the page to choose your desired model size, and then click the \"`๐Ÿ“ฆLFS  `  `  โ†“`\" button next to your desired quantization.\n\nHere is a table adapted from [TheBloke](https://huggingface.co/TheBloke) explaining the various precisions:\n\n| Quant method | Use case |\n| ---- | ---- |\n| Q2_K | significant quality loss - not recommended for most purposes |\n| Q3_K_S | very small, high quality loss |\n| Q3_K_M | very small, high quality loss |\n| Q3_K_L | small, substantial quality loss |\n| Q4_0 | legacy; small, very high quality loss - prefer using Q3_K_M |\n| Q4_K_S | small, greater quality loss |\n| Q4_K_M | medium, balanced quality - recommended |\n| Q5_0 | legacy; medium, balanced quality - prefer using Q4_K_M |\n| Q5_K_S | large, low quality loss - recommended |\n| Q5_K_M | large, very low quality loss - recommended |\n| Q6_K | very large, extremely low quality loss |\n| Q8_0 | very large, extremely low quality loss - not recommended |\n| F16 | half precision - almost identical to the original |\n| F32 | original precision - recommended by the Mamba authors |",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "merge",
    "text-generation",
    "base_model:state-spaces/mamba-1.4b",
    "base_model:merge:state-spaces/mamba-1.4b",
    "base_model:state-spaces/mamba-130m",
    "base_model:merge:state-spaces/mamba-130m",
    "base_model:state-spaces/mamba-2.8b",
    "base_model:merge:state-spaces/mamba-2.8b",
    "base_model:state-spaces/mamba-2.8b-slimpj",
    "base_model:merge:state-spaces/mamba-2.8b-slimpj",
    "base_model:state-spaces/mamba-370m",
    "base_model:merge:state-spaces/mamba-370m",
    "base_model:state-spaces/mamba-790m",
    "base_model:merge:state-spaces/mamba-790m",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us"
  ],
  "likes": 2,
  "downloads": 258,
  "gated": false,
  "private": false,
  "last_modified": "2024-03-12T20:14:30.000Z",
  "created_at": "2024-03-12T17:10:36.000Z",
  "pipeline_tag": "text-generation",
  "library_name": ""
}
Source payload excerpt (from Hugging Face API)
{
  "_id": "65f08c8c0268a75eac4fb8b3",
  "id": "devingulliver/mamba-gguf",
  "modelId": "devingulliver/mamba-gguf",
  "sha": "4f5fc95be23f5aefa5dd1ccd639eabe35c47193b",
  "createdAt": "2024-03-12T17:10:36.000Z",
  "lastModified": "2024-03-12T20:14:30.000Z",
  "author": "devingulliver",
  "downloads": 258,
  "likes": 2,
  "gated": false,
  "private": false,
  "pipeline_tag": "text-generation",
  "library_name": "",
  "siblings_count": 86
}