Instructions to use mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-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 mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-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 mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M
Use Docker
docker model run hf.co/mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf with Ollama:
ollama run hf.co/mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf with Docker Model Runner:
docker model run hf.co/mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M
- Lemonade
How to use mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf:Q4_K_M
Run and chat with the model
lemonade run user.llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf
llm-jpさんが公開しているllm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0のggufフォーマット変換版です。
モデル一覧
GGUF V2.0系
mmnga/llm-jp-13b-v2.0-gguf
mmnga/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf
mmnga/llm-jp-13b-instruct-full-ac_001-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf
mmnga/llm-jp-13b-instruct-full-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-gguf
GGUF V1.0系
mmnga/llm-jp-13b-instruct-dolly-en-ja-oasst-v1.1-gguf
mmnga/llm-jp-13b-v1.0-gguf
mmnga/llm-jp-13b-instruct-full-jaster-dolly-oasst-v1.0-gguf
mmnga/llm-jp-13b-instruct-full-dolly-oasst-v1.0-gguf
mmnga/llm-jp-1.3b-v1.0-gguf
Convert Script
convert-hf-to-gguf_llmjp_v2-py
Usage
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
make -j
./main -m 'llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0-q4_0.gguf' -n 128 -p '以下は、タスクを説明する指示です。要求を適切に満たす応答を書きなさい。\n\n### 指示:\n自然言語処理とは何か\n\n### 応答:\n' --top_p 0.95 --temp 0.7 --repeat-penalty 1.1
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