Instructions to use mradermacher/ARC-Base-8B-Condensed-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/ARC-Base-8B-Condensed-GGUF with Transformers:

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/ARC-Base-8B-Condensed-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mradermacher/ARC-Base-8B-Condensed-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 mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/ARC-Base-8B-Condensed-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 mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/ARC-Base-8B-Condensed-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 mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/ARC-Base-8B-Condensed-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 mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/ARC-Base-8B-Condensed-GGUF with Ollama:
```
ollama run hf.co/mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use mradermacher/ARC-Base-8B-Condensed-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/ARC-Base-8B-Condensed-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/ARC-Base-8B-Condensed-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.ARC-Base-8B-Condensed-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

mradermacher commited on Jan 22

Commit

13f0afc

verified ·

1 Parent(s): 09205d6

auto-patch README.md

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@@ -10,13 +10,10 @@ quantized_by: mradermacher
 tags:
 - llama
 - dense-responses
-- self-optimization
 - representation-engineering
 - cf-hot
 - recursive-self-improvement
-- mentor-mode
-- revenue-generation
-- autonomous-agent
 ---
 ## About

 tags:
 - llama
 - dense-responses
+- self-improvement
 - representation-engineering
 - cf-hot
 - recursive-self-improvement
 ---
 ## About