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mradermacher/amd-llama-135m-gguf Q5_K_S 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

mradermacher/amd-llama-135m-gguf overview

About static quants of https://huggingface.co/amd/AMD-Llama-135m weighted/imatrix quants are available at https://huggingface.co/mradermacher/AMD-Llama-135m-i1-GGUF

transformersggufendataset:cerebras/SlimPajama-627Bdataset:manu/project_gutenbergbase_model:amd/AMD-Llama-135mbase_model:quantized:amd/AMD-Llama-135mlicense:apache-2.0endpoints_compatibleregion:us
mradermacher/amd-llama-135m-gguf visual
Downloads
184
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

13 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
AMD-Llama-135m.IQ4_XS.gguf GGUF IQ4_XS 75.71 MB Download
AMD-Llama-135m.Q2_K.gguf GGUF Q2_K 57.46 MB Download
AMD-Llama-135m.Q3_K_L.gguf GGUF Q3_K_L 72.99 MB Download
AMD-Llama-135m.Q3_K_M.gguf GGUF Q3_K_M 69.20 MB Download
AMD-Llama-135m.Q3_K_S.gguf GGUF Q3_K_S 64.87 MB Download
AMD-Llama-135m.Q4_0_4_4.gguf GGUF 78.74 MB Download
AMD-Llama-135m.Q4_K_M.gguf GGUF Q4_K_M 81.93 MB Download
AMD-Llama-135m.Q4_K_S.gguf GGUF Q4_K_S 79.21 MB Download
AMD-Llama-135m.Q5_K_M.gguf GGUF Q5_K_M 93.44 MB Download
AMD-Llama-135m.Q5_K_S.gguf GGUF Q5_K_S 91.80 MB Download
AMD-Llama-135m.Q6_K.gguf GGUF Q6_K 105.67 MB Download
AMD-Llama-135m.Q8_0.gguf GGUF 136.64 MB Download
AMD-Llama-135m.f16.gguf GGUF F16 256.52 MB Download

Model Details Live

Model Slug
mradermacher/amd-llama-135m-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2024-11-14
Last Modified
2024-11-14
Gated
No
Private
No
HF SHA
ef55798db270724413be27e9e03b47860238308e
License
apache-2.0
Language
en
Base Model
amd/AMD-Llama-135m

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "amd/AMD-Llama-135m",
    "datasets": [
      "cerebras/SlimPajama-627B",
      "manu/project_gutenberg"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "amd/AMD-Llama-135m",
      "datasets": [
        "cerebras/SlimPajama-627B",
        "manu/project_gutenberg"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/amd/AMD-Llama-135m  weighted/imatrix quants are available at https://huggingface.co/mradermacher/AMD-Llama-135m-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: amd/AMD-Llama-135m\ndatasets:\n- cerebras/SlimPajama-627B\n- manu/project_gutenberg\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\nstatic quants of https://huggingface.co/amd/AMD-Llama-135m\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/AMD-Llama-135m-i1-GGUF\n## Usage\n\nIf you are unsure how to use GGUF files, refer to one of [TheBloke's\nREADMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for\nmore details, including on how to concatenate multi-part files.\n\n## Provided Quants\n\n(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)\n\n| Link | Type | Size/GB | Notes |\n|:-----|:-----|--------:|:------|\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q2_K.gguf) | Q2_K | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q3_K_S.gguf) | Q3_K_S | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q3_K_M.gguf) | Q3_K_M | 0.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q3_K_L.gguf) | Q3_K_L | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.IQ4_XS.gguf) | IQ4_XS | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q4_0_4_4.gguf) | Q4_0_4_4 | 0.2 | fast on arm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q4_K_S.gguf) | Q4_K_S | 0.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q4_K_M.gguf) | Q4_K_M | 0.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q5_K_S.gguf) | Q5_K_S | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q5_K_M.gguf) | Q5_K_M | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q6_K.gguf) | Q6_K | 0.2 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.Q8_0.gguf) | Q8_0 | 0.2 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/AMD-Llama-135m-GGUF/resolve/main/AMD-Llama-135m.f16.gguf) | f16 | 0.4 | 16 bpw, overkill |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\n\nAnd here are Artefact2's thoughts on the matter:\nhttps://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9\n\n## FAQ / Model Request\n\nSee https://huggingface.co/mradermacher/model_requests for some answers to\nquestions you might have and/or if you want some other model quantized.\n\n## Thanks\n\nI thank my company, [nethype GmbH](https://www.nethype.de/), for letting\nme use its servers and providing upgrades to my workstation to enable\nthis work in my free time.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "en",
    "dataset:cerebras/SlimPajama-627B",
    "dataset:manu/project_gutenberg",
    "base_model:amd/AMD-Llama-135m",
    "base_model:quantized:amd/AMD-Llama-135m",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us"
  ],
  "likes": 0,
  "downloads": 184,
  "gated": false,
  "private": false,
  "last_modified": "2024-11-14T21:48:31.000Z",
  "created_at": "2024-11-14T05:57:52.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
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  "id": "mradermacher/AMD-Llama-135m-GGUF",
  "modelId": "mradermacher/AMD-Llama-135m-GGUF",
  "sha": "ef55798db270724413be27e9e03b47860238308e",
  "createdAt": "2024-11-14T05:57:52.000Z",
  "lastModified": "2024-11-14T21:48:31.000Z",
  "author": "mradermacher",
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