mmnga/tokyotech-llm-llama-3.1-swallow-70b-instruct-v0.3-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
mmnga/tokyotech-llm-llama-3.1-swallow-70b-instruct-v0.3-gguf overview
tokyotech-llmさんが公開しているLlama-3.1-Swallow-70B-Instruct-v0.3のggufフォーマット変換版です。 imatrixのデータはTFMC/imatrix-dataset-for-japanese-llmを使用して作成しました。
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102
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2
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Library
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Visibility
Public
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Repository Files & Downloads
21 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ1_M.gguf | GGUF | IQ1_M | 15.60 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ1_S.gguf | GGUF | IQ1_S | 14.29 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ2_M.gguf | GGUF | IQ2_M | 22.46 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ2_S.gguf | GGUF | IQ2_S | 20.71 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ2_XS.gguf | GGUF | IQ2_XS | 19.69 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ2_XXS.gguf | GGUF | IQ2_XXS | 17.79 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ3_M.gguf | GGUF | IQ3_M | 29.74 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ3_S.gguf | GGUF | IQ3_S | 28.79 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ3_XS.gguf | GGUF | IQ3_XS | 27.29 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ3_XXS.gguf | GGUF | IQ3_XXS | 25.58 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ4_NL.gguf | GGUF | IQ4_NL | 37.30 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-IQ4_XS.gguf | GGUF | IQ4_XS | 35.30 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q2_K.gguf | GGUF | Q2_K | 24.56 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q3_K_L.gguf | GGUF | Q3_K_L | 34.59 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q3_K_M.gguf | GGUF | Q3_K_M | 31.91 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q3_K_S.gguf | GGUF | Q3_K_S | 28.79 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q4_0.gguf | GGUF | — | 37.22 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q4_K_M.gguf | GGUF | Q4_K_M | 39.60 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q4_K_S.gguf | GGUF | Q4_K_S | 37.58 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q5_0.gguf | GGUF | — | 45.32 GB | Download |
| tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q5_K_S.gguf | GGUF | Q5_K_S | 45.32 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"license": "llama3.1",
"language": [
"en",
"ja"
],
"datasets": [
"TFMC/imatrix-dataset-for-japanese-llm"
],
"base_model": [
"tokyotech-llm/Llama-3.1-Swallow-70B-Instruct-v0.3"
],
"frontmatter": {
"license": "llama3.1",
"language": [
"en",
"ja"
],
"datasets": [
"TFMC/imatrix-dataset-for-japanese-llm"
],
"base_model": [
"tokyotech-llm/Llama-3.1-Swallow-70B-Instruct-v0.3"
]
},
"hero_image_url": "",
"summary": "tokyotech-llmさんが公開しているLlama-3.1-Swallow-70B-Instruct-v0.3のggufフォーマット変換版です。 imatrixのデータはTFMC/imatrix-dataset-for-japanese-llmを使用して作成しました。",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nlicense: llama3.1\nlanguage:\n- en\n- ja\ndatasets:\n- TFMC/imatrix-dataset-for-japanese-llm\nbase_model:\n- tokyotech-llm/Llama-3.1-Swallow-70B-Instruct-v0.3\n---\n\n# tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-gguf\n[tokyotech-llmさんが公開しているLlama-3.1-Swallow-70B-Instruct-v0.3](https://huggingface.co/tokyotech-llm/Llama-3.1-Swallow-70B-Instruct-v0.3)のggufフォーマット変換版です。 \n\nimatrixのデータは[TFMC/imatrix-dataset-for-japanese-llm](https://huggingface.co/datasets/TFMC/imatrix-dataset-for-japanese-llm)を使用して作成しました。 \n \n## Usage\n\n```\ngit clone https://github.com/ggerganov/llama.cpp.git\ncd llama.cpp\ncmake -B build -DGGML_CUDA=ON\ncmake --build build --config Release\nbuild/bin/llama-cli -m 'tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-Q4_0.gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv\n```",
"related_quantizations": []
},
"tags": [
"gguf",
"en",
"ja",
"dataset:TFMC/imatrix-dataset-for-japanese-llm",
"base_model:tokyotech-llm/Llama-3.1-Swallow-70B-Instruct-v0.3",
"base_model:quantized:tokyotech-llm/Llama-3.1-Swallow-70B-Instruct-v0.3",
"license:llama3.1",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 2,
"downloads": 102,
"gated": false,
"private": false,
"last_modified": "2024-12-30T19:31:26.000Z",
"created_at": "2024-12-30T07:17:56.000Z",
"pipeline_tag": "",
"library_name": ""
}
Source payload excerpt (from Hugging Face API)
{
"_id": "67724924afe9fcdc2186da90",
"id": "mmnga/tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-gguf",
"modelId": "mmnga/tokyotech-llm-Llama-3.1-Swallow-70B-Instruct-v0.3-gguf",
"sha": "9a4c02bcc49babe9c578ca0557090bc15b0f9447",
"createdAt": "2024-12-30T07:17:56.000Z",
"lastModified": "2024-12-30T19:31:26.000Z",
"author": "mmnga",
"downloads": 102,
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"gated": false,
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"siblings_count": 29
}