Model Intelligence Sheet
mradermacher/koishi-8x7b-qlora-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/ewof/koishi-8x7b-qlora static quants are available at https://huggingface.co/mradermacher/koishi-8x7b-qlora-GGUF
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Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
21 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| koishi-8x7b-qlora.i1-IQ1_M.gguf | GGUF | IQ1_M | 10.10 GB | Download |
| koishi-8x7b-qlora.i1-IQ1_S.gguf | GGUF | IQ1_S | 9.15 GB | Download |
| koishi-8x7b-qlora.i1-IQ2_M.gguf | GGUF | IQ2_M | 14.43 GB | Download |
| koishi-8x7b-qlora.i1-IQ2_S.gguf | GGUF | IQ2_S | 13.16 GB | Download |
| koishi-8x7b-qlora.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 12.97 GB | Download |
| koishi-8x7b-qlora.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 11.69 GB | Download |
| koishi-8x7b-qlora.i1-IQ3_M.gguf | GGUF | IQ3_M | 19.96 GB | Download |
| koishi-8x7b-qlora.i1-IQ3_S.gguf | GGUF | IQ3_S | 19.03 GB | Download |
| koishi-8x7b-qlora.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 18.02 GB | Download |
| koishi-8x7b-qlora.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 16.99 GB | Download |
| koishi-8x7b-qlora.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 23.36 GB | Download |
| koishi-8x7b-qlora.i1-Q2_K.gguf | GGUF | Q2_K | 16.12 GB | Download |
| koishi-8x7b-qlora.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 22.51 GB | Download |
| koishi-8x7b-qlora.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 21.00 GB | Download |
| koishi-8x7b-qlora.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 19.03 GB | Download |
| koishi-8x7b-qlora.i1-Q4_0.gguf | GGUF | — | 24.74 GB | Download |
| koishi-8x7b-qlora.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 26.49 GB | Download |
| koishi-8x7b-qlora.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 24.91 GB | Download |
| koishi-8x7b-qlora.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 30.95 GB | Download |
| koishi-8x7b-qlora.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 30.02 GB | Download |
| koishi-8x7b-qlora.i1-Q6_K.gguf | GGUF | Q6_K | 35.75 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "ewof/koishi-8x7b-qlora",
"datasets": [
"ewof/koishi-instruct-metharme"
],
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "ewof/koishi-8x7b-qlora",
"datasets": [
"ewof/koishi-instruct-metharme"
],
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher"
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About weighted/imatrix quants of https://huggingface.co/ewof/koishi-8x7b-qlora static quants are available at https://huggingface.co/mradermacher/koishi-8x7b-qlora-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: ewof/koishi-8x7b-qlora\ndatasets:\n- ewof/koishi-instruct-metharme\nlanguage:\n- en\nlibrary_name: transformers\nquantized_by: mradermacher\n---\n## About\n\n<!-- ### quantize_version: 1 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: -->\n<!-- ### vocab_type: -->\nweighted/imatrix quants of https://huggingface.co/ewof/koishi-8x7b-qlora\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/koishi-8x7b-qlora-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/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ1_S.gguf) | i1-IQ1_S | 9.9 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ1_M.gguf) | i1-IQ1_M | 10.9 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 12.7 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ2_XS.gguf) | i1-IQ2_XS | 14.0 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ2_S.gguf) | i1-IQ2_S | 14.2 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ2_M.gguf) | i1-IQ2_M | 15.6 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q2_K.gguf) | i1-Q2_K | 17.4 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 18.3 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ3_XS.gguf) | i1-IQ3_XS | 19.5 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ3_S.gguf) | i1-IQ3_S | 20.5 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q3_K_S.gguf) | i1-Q3_K_S | 20.5 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ3_M.gguf) | i1-IQ3_M | 21.5 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q3_K_M.gguf) | i1-Q3_K_M | 22.6 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q3_K_L.gguf) | i1-Q3_K_L | 24.3 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-IQ4_XS.gguf) | i1-IQ4_XS | 25.2 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q4_0.gguf) | i1-Q4_0 | 26.7 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q4_K_S.gguf) | i1-Q4_K_S | 26.8 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q4_K_M.gguf) | i1-Q4_K_M | 28.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q5_K_S.gguf) | i1-Q5_K_S | 32.3 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q5_K_M.gguf) | i1-Q5_K_M | 33.3 | |\n| [GGUF](https://huggingface.co/mradermacher/koishi-8x7b-qlora-i1-GGUF/resolve/main/koishi-8x7b-qlora.i1-Q6_K.gguf) | i1-Q6_K | 38.5 | practically like static Q6_K |\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",
"en",
"dataset:ewof/koishi-instruct-metharme",
"base_model:ewof/koishi-8x7b-qlora",
"base_model:quantized:ewof/koishi-8x7b-qlora",
"endpoints_compatible",
"region:us"
],
"likes": 0,
"downloads": 995,
"gated": false,
"private": false,
"last_modified": "2024-05-05T15:13:38.000Z",
"created_at": "2024-04-23T18:37:50.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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"sha": "a5cb88eed5d986a93d99aa4ab03d478bf08ce1d1",
"createdAt": "2024-04-23T18:37:50.000Z",
"lastModified": "2024-05-05T15:13:38.000Z",
"author": "mradermacher",
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