Model Intelligence Sheet
mradermacher/standard-loss-llama-1b-gguf overview
About static quants of https://huggingface.co/tomg-group-umd/standard-loss-llama-1B weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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transformers
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Repository Files & Downloads
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Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| standard-loss-llama-1B.IQ3_M.gguf | GGUF | IQ3_M | 492.28 MB | Download |
| standard-loss-llama-1B.IQ3_S.gguf | GGUF | IQ3_S | 477.67 MB | Download |
| standard-loss-llama-1B.IQ3_XS.gguf | GGUF | IQ3_XS | 455.50 MB | Download |
| standard-loss-llama-1B.IQ4_XS.gguf | GGUF | IQ4_XS | 581.56 MB | Download |
| standard-loss-llama-1B.Q2_K.gguf | GGUF | Q2_K | 412.11 MB | Download |
| standard-loss-llama-1B.Q3_K_L.gguf | GGUF | Q3_K_L | 564.12 MB | Download |
| standard-loss-llama-1B.Q3_K_M.gguf | GGUF | Q3_K_M | 523.00 MB | Download |
| standard-loss-llama-1B.Q3_K_S.gguf | GGUF | Q3_K_S | 476.21 MB | Download |
| standard-loss-llama-1B.Q4_K_M.gguf | GGUF | Q4_K_M | 636.88 MB | Download |
| standard-loss-llama-1B.Q4_K_S.gguf | GGUF | Q4_K_S | 610.23 MB | Download |
| standard-loss-llama-1B.Q5_K_M.gguf | GGUF | Q5_K_M | 745.82 MB | Download |
| standard-loss-llama-1B.Q5_K_S.gguf | GGUF | Q5_K_S | 730.54 MB | Download |
| standard-loss-llama-1B.Q6_K.gguf | GGUF | Q6_K | 861.56 MB | Download |
| standard-loss-llama-1B.Q8_0.gguf | GGUF | — | 1.09 GB | Download |
| standard-loss-llama-1B.f16.gguf | GGUF | F16 | 2.05 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "tomg-group-umd/standard-loss-llama-1B",
"datasets": [
"tomg-group-umd/wikipedia-en-2k-samples"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"goldfish-loss",
"memorization",
"mitigation"
],
"frontmatter": {
"base_model": "tomg-group-umd/standard-loss-llama-1B",
"datasets": [
"tomg-group-umd/wikipedia-en-2k-samples"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"goldfish-loss",
"memorization",
"mitigation"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/tomg-group-umd/standard-loss-llama-1B weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: tomg-group-umd/standard-loss-llama-1B\ndatasets:\n- tomg-group-umd/wikipedia-en-2k-samples\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- goldfish-loss\n- memorization\n- mitigation\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/tomg-group-umd/standard-loss-llama-1B\n\n<!-- provided-files -->\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\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/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q2_K.gguf) | Q2_K | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.IQ3_XS.gguf) | IQ3_XS | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q3_K_S.gguf) | Q3_K_S | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.IQ3_S.gguf) | IQ3_S | 0.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.IQ3_M.gguf) | IQ3_M | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q3_K_M.gguf) | Q3_K_M | 0.6 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q3_K_L.gguf) | Q3_K_L | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.IQ4_XS.gguf) | IQ4_XS | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q4_K_S.gguf) | Q4_K_S | 0.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q4_K_M.gguf) | Q4_K_M | 0.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q5_K_S.gguf) | Q5_K_S | 0.9 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q5_K_M.gguf) | Q5_K_M | 0.9 | |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q6_K.gguf) | Q6_K | 1.0 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.Q8_0.gguf) | Q8_0 | 1.3 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/standard-loss-llama-1B-GGUF/resolve/main/standard-loss-llama-1B.f16.gguf) | f16 | 2.3 | 16 bpw, overkill |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n\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",
"goldfish-loss",
"memorization",
"mitigation",
"en",
"dataset:tomg-group-umd/wikipedia-en-2k-samples",
"base_model:tomg-group-umd/standard-loss-llama-1B",
"base_model:quantized:tomg-group-umd/standard-loss-llama-1B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
],
"likes": 0,
"downloads": 110,
"gated": false,
"private": false,
"last_modified": "2024-08-20T12:52:59.000Z",
"created_at": "2024-08-20T12:35:57.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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"_id": "66c48dad2646b9241c35ffd0",
"id": "mradermacher/standard-loss-llama-1B-GGUF",
"modelId": "mradermacher/standard-loss-llama-1B-GGUF",
"sha": "21b9c1542e4cd6ed4db15b77778b9c36d7ab3b58",
"createdAt": "2024-08-20T12:35:57.000Z",
"lastModified": "2024-08-20T12:52:59.000Z",
"author": "mradermacher",
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