Instructions to use RichardErkhov/appvoid_-_arco-2-instruct-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 RichardErkhov/appvoid_-_arco-2-instruct-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 RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/appvoid_-_arco-2-instruct-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 RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M
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 RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M
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 RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M
Use Docker
docker model run hf.co/RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use RichardErkhov/appvoid_-_arco-2-instruct-gguf with Ollama:
ollama run hf.co/RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use RichardErkhov/appvoid_-_arco-2-instruct-gguf with Docker Model Runner:
docker model run hf.co/RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M
- Lemonade
How to use RichardErkhov/appvoid_-_arco-2-instruct-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RichardErkhov/appvoid_-_arco-2-instruct-gguf:Q4_K_M
Run and chat with the model
lemonade run user.appvoid_-_arco-2-instruct-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Quantization made by Richard Erkhov.
arco-2-instruct - GGUF
- Model creator: https://huggingface.co/appvoid/
- Original model: https://huggingface.co/appvoid/arco-2-instruct/
| Name | Quant method | Size |
|---|---|---|
| arco-2-instruct.Q2_K.gguf | Q2_K | 0.2GB |
| arco-2-instruct.IQ3_XS.gguf | IQ3_XS | 0.22GB |
| arco-2-instruct.IQ3_S.gguf | IQ3_S | 0.22GB |
| arco-2-instruct.Q3_K_S.gguf | Q3_K_S | 0.22GB |
| arco-2-instruct.IQ3_M.gguf | IQ3_M | 0.23GB |
| arco-2-instruct.Q3_K.gguf | Q3_K | 0.24GB |
| arco-2-instruct.Q3_K_M.gguf | Q3_K_M | 0.24GB |
| arco-2-instruct.Q3_K_L.gguf | Q3_K_L | 0.26GB |
| arco-2-instruct.IQ4_XS.gguf | IQ4_XS | 0.27GB |
| arco-2-instruct.Q4_0.gguf | Q4_0 | 0.28GB |
| arco-2-instruct.IQ4_NL.gguf | IQ4_NL | 0.28GB |
| arco-2-instruct.Q4_K_S.gguf | Q4_K_S | 0.28GB |
| arco-2-instruct.Q4_K.gguf | Q4_K | 0.3GB |
| arco-2-instruct.Q4_K_M.gguf | Q4_K_M | 0.3GB |
| arco-2-instruct.Q4_1.gguf | Q4_1 | 0.31GB |
| arco-2-instruct.Q5_0.gguf | Q5_0 | 0.34GB |
| arco-2-instruct.Q5_K_S.gguf | Q5_K_S | 0.34GB |
| arco-2-instruct.Q5_K.gguf | Q5_K | 0.34GB |
| arco-2-instruct.Q5_K_M.gguf | Q5_K_M | 0.34GB |
| arco-2-instruct.Q5_1.gguf | Q5_1 | 0.36GB |
| arco-2-instruct.Q6_K.gguf | Q6_K | 0.39GB |
| arco-2-instruct.Q8_0.gguf | Q8_0 | 0.51GB |
Original model description:
base_model: - appvoid/palmer-004-turbo - appvoid/text-arco - appvoid/arco-2 - appvoid/arco-reflection - appvoid/arco-2-reasoning-20k library_name: transformers tags: - mergekit - merge license: apache-2.0
this model was not trained, it is a merged of experts to improve instruction following tasks and reasoning.
prompt
there is no prompt intentionally set.
supporters
trivia
arco-2-instruct (codenamed as arco-exp-17) is a merge of reflection models that improved instruction accuracy a little better than the original one.
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