mradermacher/berghof-erp-7b-gguf Q4_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/berghof-erp-7b-gguf overview
About static quants of https://huggingface.co/Elizezen/Berghof-ERP-7B weighted/imatrix quants are available at https://huggingface.co/mradermacher/Berghof-ERP-7B-i1-GGUF
Downloads
467
Likes
6
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
15 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Berghof-ERP-7B.IQ3_M.gguf | GGUF | IQ3_M | 3.06 GB | Download |
| Berghof-ERP-7B.IQ3_S.gguf | GGUF | IQ3_S | 2.96 GB | Download |
| Berghof-ERP-7B.IQ3_XS.gguf | GGUF | IQ3_XS | 2.81 GB | Download |
| Berghof-ERP-7B.IQ4_XS.gguf | GGUF | IQ4_XS | 3.67 GB | Download |
| Berghof-ERP-7B.Q2_K.gguf | GGUF | Q2_K | 2.53 GB | Download |
| Berghof-ERP-7B.Q3_K_L.gguf | GGUF | Q3_K_L | 3.56 GB | Download |
| Berghof-ERP-7B.Q3_K_M.gguf | GGUF | Q3_K_M | 3.28 GB | Download |
| Berghof-ERP-7B.Q3_K_S.gguf | GGUF | Q3_K_S | 2.95 GB | Download |
| Berghof-ERP-7B.Q4_K_M.gguf | GGUF | Q4_K_M | 4.07 GB | Download |
| Berghof-ERP-7B.Q4_K_S.gguf | GGUF | Q4_K_S | 3.86 GB | Download |
| Berghof-ERP-7B.Q5_K_M.gguf | GGUF | Q5_K_M | 4.78 GB | Download |
| Berghof-ERP-7B.Q5_K_S.gguf | GGUF | Q5_K_S | 4.65 GB | Download |
| Berghof-ERP-7B.Q6_K.gguf | GGUF | Q6_K | 5.53 GB | Download |
| Berghof-ERP-7B.Q8_0.gguf | GGUF | — | 7.17 GB | Download |
| Berghof-ERP-7B.f16.gguf | GGUF | F16 | 13.49 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "Elizezen/Berghof-ERP-7B",
"language": [
"ja"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"tags": [
"causal-lm",
"not-for-all-audiences",
"nsfw"
],
"frontmatter": {
"base_model": "Elizezen/Berghof-ERP-7B",
"language": [
"ja"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"tags": [
"causal-lm",
"not-for-all-audiences",
"nsfw"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/Elizezen/Berghof-ERP-7B weighted/imatrix quants are available at https://huggingface.co/mradermacher/Berghof-ERP-7B-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: Elizezen/Berghof-ERP-7B\nlanguage:\n- ja\nlibrary_name: transformers\nquantized_by: mradermacher\ntags:\n- causal-lm\n- not-for-all-audiences\n- nsfw\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/Elizezen/Berghof-ERP-7B\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Berghof-ERP-7B-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/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q2_K.gguf) | Q2_K | 2.8 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.IQ3_XS.gguf) | IQ3_XS | 3.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q3_K_S.gguf) | Q3_K_S | 3.3 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.IQ3_S.gguf) | IQ3_S | 3.3 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.IQ3_M.gguf) | IQ3_M | 3.4 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q3_K_L.gguf) | Q3_K_L | 3.9 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.IQ4_XS.gguf) | IQ4_XS | 4.0 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q5_K_S.gguf) | Q5_K_S | 5.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q5_K_M.gguf) | Q5_K_M | 5.2 | |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q6_K.gguf) | Q6_K | 6.0 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Berghof-ERP-7B-GGUF/resolve/main/Berghof-ERP-7B.f16.gguf) | f16 | 14.6 | 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",
"causal-lm",
"not-for-all-audiences",
"nsfw",
"ja",
"base_model:Elizezen/Berghof-ERP-7B",
"base_model:quantized:Elizezen/Berghof-ERP-7B",
"endpoints_compatible",
"region:us"
],
"likes": 6,
"downloads": 467,
"gated": false,
"private": false,
"last_modified": "2024-06-22T01:24:33.000Z",
"created_at": "2024-06-21T13:57:31.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
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"id": "mradermacher/Berghof-ERP-7B-GGUF",
"modelId": "mradermacher/Berghof-ERP-7B-GGUF",
"sha": "41b6cf4105ffeeacfb3f0c7bb7ae04cd57946e6f",
"createdAt": "2024-06-21T13:57:31.000Z",
"lastModified": "2024-06-22T01:24:33.000Z",
"author": "mradermacher",
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}