Instructions to use tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
- LM Studio
- Jan
- vLLM
How to use tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
- Ollama
How to use tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF with Ollama:
ollama run hf.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
- Lemonade
How to use tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF:Q2_K
Run and chat with the model
lemonade run user.llama3.1_korean_v0.1_sft_by_aidx-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- README.md +84 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q2_K.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q3_K_L.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q3_K_M.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q3_K_S.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q4_0.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q4_K_M.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q4_K_S.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q5_0.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q5_K_M.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q5_K_S.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q6_K.gguf +3 -0
- llama3.1_korean_v0.1_sft_by_aidx-Q8_0.gguf +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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llama3.1_korean_v0.1_sft_by_aidx-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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| 47 |
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llama3.1_korean_v0.1_sft_by_aidx-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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| 1 |
+
---
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| 2 |
+
license: apache-2.0
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language:
|
| 4 |
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- ko
|
| 5 |
+
- en
|
| 6 |
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base_model: SEOKDONG/llama3.1_korean_v0.1_sft_by_aidx
|
| 7 |
+
pipeline_tag: text-generation
|
| 8 |
+
datasets:
|
| 9 |
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- AIDX-ktds/ko_leaderboard
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+
tags:
|
| 11 |
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- ktds
|
| 12 |
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- ko
|
| 13 |
+
- ko_leaderboard
|
| 14 |
+
- korean
|
| 15 |
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- TensorBlock
|
| 16 |
+
- GGUF
|
| 17 |
+
---
|
| 18 |
+
|
| 19 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
|
| 20 |
+
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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| 21 |
+
</div>
|
| 22 |
+
<div style="display: flex; justify-content: space-between; width: 100%;">
|
| 23 |
+
<div style="display: flex; flex-direction: column; align-items: flex-start;">
|
| 24 |
+
<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
| 25 |
+
Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
|
| 26 |
+
</p>
|
| 27 |
+
</div>
|
| 28 |
+
</div>
|
| 29 |
+
|
| 30 |
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## SEOKDONG/llama3.1_korean_v0.1_sft_by_aidx - GGUF
|
| 31 |
+
|
| 32 |
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This repo contains GGUF format model files for [SEOKDONG/llama3.1_korean_v0.1_sft_by_aidx](https://huggingface.co/SEOKDONG/llama3.1_korean_v0.1_sft_by_aidx).
|
| 33 |
+
|
| 34 |
+
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
|
| 35 |
+
|
| 36 |
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## Prompt template
|
| 37 |
+
|
| 38 |
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```
|
| 39 |
+
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
|
| 40 |
+
|
| 41 |
+
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
|
| 42 |
+
|
| 43 |
+
{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
|
| 44 |
+
```
|
| 45 |
+
|
| 46 |
+
## Model file specification
|
| 47 |
+
|
| 48 |
+
| Filename | Quant type | File Size | Description |
|
| 49 |
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| -------- | ---------- | --------- | ----------- |
|
| 50 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q2_K.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q2_K.gguf) | Q2_K | 2.961 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 51 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q3_K_S.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q3_K_S.gguf) | Q3_K_S | 3.413 GB | very small, high quality loss |
|
| 52 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q3_K_M.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q3_K_M.gguf) | Q3_K_M | 3.743 GB | very small, high quality loss |
|
| 53 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q3_K_L.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q3_K_L.gguf) | Q3_K_L | 4.025 GB | small, substantial quality loss |
|
| 54 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q4_0.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q4_0.gguf) | Q4_0 | 4.341 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 55 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q4_K_S.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q4_K_S.gguf) | Q4_K_S | 4.370 GB | small, greater quality loss |
|
| 56 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q4_K_M.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q4_K_M.gguf) | Q4_K_M | 4.583 GB | medium, balanced quality - recommended |
|
| 57 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q5_0.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q5_0.gguf) | Q5_0 | 5.215 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 58 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q5_K_S.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q5_K_S.gguf) | Q5_K_S | 5.215 GB | large, low quality loss - recommended |
|
| 59 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q5_K_M.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q5_K_M.gguf) | Q5_K_M | 5.339 GB | large, very low quality loss - recommended |
|
| 60 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q6_K.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q6_K.gguf) | Q6_K | 6.143 GB | very large, extremely low quality loss |
|
| 61 |
+
| [llama3.1_korean_v0.1_sft_by_aidx-Q8_0.gguf](https://huggingface.co/tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF/tree/main/llama3.1_korean_v0.1_sft_by_aidx-Q8_0.gguf) | Q8_0 | 7.954 GB | very large, extremely low quality loss - not recommended |
|
| 62 |
+
|
| 63 |
+
|
| 64 |
+
## Downloading instruction
|
| 65 |
+
|
| 66 |
+
### Command line
|
| 67 |
+
|
| 68 |
+
Firstly, install Huggingface Client
|
| 69 |
+
|
| 70 |
+
```shell
|
| 71 |
+
pip install -U "huggingface_hub[cli]"
|
| 72 |
+
```
|
| 73 |
+
|
| 74 |
+
Then, downoad the individual model file the a local directory
|
| 75 |
+
|
| 76 |
+
```shell
|
| 77 |
+
huggingface-cli download tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF --include "llama3.1_korean_v0.1_sft_by_aidx-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
| 78 |
+
```
|
| 79 |
+
|
| 80 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
| 81 |
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|
| 82 |
+
```shell
|
| 83 |
+
huggingface-cli download tensorblock/llama3.1_korean_v0.1_sft_by_aidx-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
| 84 |
+
```
|
llama3.1_korean_v0.1_sft_by_aidx-Q2_K.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:012d351aab0446e34f9cf0c0c21ddaec162d14b28ecaa1f035d0ef05c30b9fac
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size 3179131776
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llama3.1_korean_v0.1_sft_by_aidx-Q3_K_L.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:620198f792c91830ccaf2a9ecfb9c23e3d062203dbf0c990d5b36bf47705a104
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| 3 |
+
size 4321956736
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llama3.1_korean_v0.1_sft_by_aidx-Q3_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:4d7f7d461b1d2fad310040c9d590859b46c3e9a8441c3ee4e8acdd1697685f49
|
| 3 |
+
size 4018918272
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llama3.1_korean_v0.1_sft_by_aidx-Q3_K_S.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:fe5e2585b6be6177ba589db091c08d6a4579d66ab148215586120070f2b18677
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| 3 |
+
size 3664499584
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llama3.1_korean_v0.1_sft_by_aidx-Q4_0.gguf
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:cd6dfa82b28bb34d2368d76cd4f6397bfccd6c23939a45b7981a8963482a5317
|
| 3 |
+
size 4661212032
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llama3.1_korean_v0.1_sft_by_aidx-Q4_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:3f596665d5c8313c80abb58bade8e46fafaedbd6cb86eea59eeca87ff6cf4e80
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