mradermacher/eurollm-1.7b-instruct-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/eurollm-1.7b-instruct-gguf overview
About static quants of https://huggingface.co/utter-project/EuroLLM-1.7B-Instruct 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.
Downloads
177
Likes
3
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
15 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| EuroLLM-1.7B-Instruct.IQ3_M.gguf | GGUF | IQ3_M | 803.39 MB | Download |
| EuroLLM-1.7B-Instruct.IQ3_S.gguf | GGUF | IQ3_S | 779.88 MB | Download |
| EuroLLM-1.7B-Instruct.IQ3_XS.gguf | GGUF | IQ3_XS | 754.57 MB | Download |
| EuroLLM-1.7B-Instruct.IQ4_XS.gguf | GGUF | IQ4_XS | 920.11 MB | Download |
| EuroLLM-1.7B-Instruct.Q2_K.gguf | GGUF | Q2_K | 686.24 MB | Download |
| EuroLLM-1.7B-Instruct.Q3_K_L.gguf | GGUF | Q3_K_L | 885.07 MB | Download |
| EuroLLM-1.7B-Instruct.Q3_K_M.gguf | GGUF | Q3_K_M | 835.94 MB | Download |
| EuroLLM-1.7B-Instruct.Q3_K_S.gguf | GGUF | Q3_K_S | 779.88 MB | Download |
| EuroLLM-1.7B-Instruct.Q4_K_M.gguf | GGUF | Q4_K_M | 996.74 MB | Download |
| EuroLLM-1.7B-Instruct.Q4_K_S.gguf | GGUF | Q4_K_S | 961.65 MB | Download |
| EuroLLM-1.7B-Instruct.Q5_K_M.gguf | GGUF | Q5_K_M | 1.12 GB | Download |
| EuroLLM-1.7B-Instruct.Q5_K_S.gguf | GGUF | Q5_K_S | 1.10 GB | Download |
| EuroLLM-1.7B-Instruct.Q6_K.gguf | GGUF | Q6_K | 1.27 GB | Download |
| EuroLLM-1.7B-Instruct.Q8_0.gguf | GGUF | — | 1.64 GB | Download |
| EuroLLM-1.7B-Instruct.f16.gguf | GGUF | F16 | 3.09 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
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"metadata": {},
"card_data": {
"base_model": "utter-project/EuroLLM-1.7B-Instruct",
"language": [
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"license": "apache-2.0",
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"frontmatter": {
"base_model": "utter-project/EuroLLM-1.7B-Instruct",
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"summary": "## About static quants of https://huggingface.co/utter-project/EuroLLM-1.7B-Instruct 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: utter-project/EuroLLM-1.7B-Instruct\nlanguage:\n- en\n- de\n- es\n- fr\n- it\n- pt\n- pl\n- nl\n- tr\n- sv\n- cs\n- el\n- hu\n- ro\n- fi\n- uk\n- sl\n- sk\n- da\n- lt\n- lv\n- et\n- bg\n- no\n- ca\n- hr\n- ga\n- mt\n- gl\n- zh\n- ru\n- ko\n- ja\n- ar\n- hi\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- generated_from_trainer\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/utter-project/EuroLLM-1.7B-Instruct\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/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q2_K.gguf) | Q2_K | 0.8 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.IQ3_XS.gguf) | IQ3_XS | 0.9 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.IQ3_S.gguf) | IQ3_S | 0.9 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q3_K_S.gguf) | Q3_K_S | 0.9 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.IQ3_M.gguf) | IQ3_M | 0.9 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q3_K_M.gguf) | Q3_K_M | 1.0 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q3_K_L.gguf) | Q3_K_L | 1.0 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.IQ4_XS.gguf) | IQ4_XS | 1.1 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q4_K_S.gguf) | Q4_K_S | 1.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q5_K_S.gguf) | Q5_K_S | 1.3 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q5_K_M.gguf) | Q5_K_M | 1.3 | |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q6_K.gguf) | Q6_K | 1.5 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.Q8_0.gguf) | Q8_0 | 1.9 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/EuroLLM-1.7B-Instruct-GGUF/resolve/main/EuroLLM-1.7B-Instruct.f16.gguf) | f16 | 3.4 | 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",
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"base_model:utter-project/EuroLLM-1.7B-Instruct",
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"license:apache-2.0",
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"likes": 3,
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"last_modified": "2024-09-25T10:41:18.000Z",
"created_at": "2024-09-24T23:58:36.000Z",
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Source payload excerpt (from Hugging Face API)
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