Instructions to use DreamBlooms/Linnaeus-0.1.0-2B-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 DreamBlooms/Linnaeus-0.1.0-2B-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 DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf DreamBlooms/Linnaeus-0.1.0-2B-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 DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf DreamBlooms/Linnaeus-0.1.0-2B-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 DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf DreamBlooms/Linnaeus-0.1.0-2B-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 DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use DreamBlooms/Linnaeus-0.1.0-2B-GGUF with Ollama:
ollama run hf.co/DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use DreamBlooms/Linnaeus-0.1.0-2B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use DreamBlooms/Linnaeus-0.1.0-2B-GGUF with Docker Model Runner:
docker model run hf.co/DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
- Lemonade
How to use DreamBlooms/Linnaeus-0.1.0-2B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Linnaeus-0.1.0-2B-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use DreamBlooms/Linnaeus-0.1.0-2B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use DreamBlooms/Linnaeus-0.1.0-2B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "DreamBlooms/Linnaeus-0.1.0-2B-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 1,461 Bytes
a1efc75 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | {
"format_version": 1,
"project": "linnaeus",
"distribution": "linnaeus",
"version": "0.1.0",
"model_id": "Linnaeus-0.1.0-2B",
"base_model": "Qwen/Qwen3.5-2B",
"base_path": ".cache/models/Qwen3.5-2B",
"base_revision": "15852e8c16360a2fea060d615a32b45270f8a8fc",
"adapter": "qwen3.5",
"lora_rank": 8,
"image_pixels": 262144,
"max_length": 2048,
"backend": {
"linear_patch": true,
"triton_convolution": true,
"experimental_rocm_sdpa": true,
"fused_norm_and_swiglu": true,
"shared_prefix": true,
"frozen_vision_cache_MiB": 128
},
"inference": "merged LoRA, BF16, fused operations, shared-prefix parallel candidate scoring",
"source_hashes": {
"train": "4e8b258c9e5d5a98810868df5d572a824a9d1d6c5aa557ab5123cb7aab5de373",
"dev": "b736750efff3e30ae8a7772c482fa248899b8a1cf69ace104310e2540671d552",
"calibration": "815cfe0855dd5494f9def19ddb2a6b12e4116c3ae24d2775db620021dd07fb28",
"test": "fdac64d536d67c011d55d00352f0be71fa3bdfb7811c0be0e05a5d66cec98095"
},
"selected_run": "runs/2b/seed-42",
"selected_step": 2800,
"selection": "maximum development macro accuracy within the run; no test selection",
"seed": 42,
"dev_macro_accuracy": 0.802734375,
"temperatures": {
"choice": 1.6947466135025024,
"noul": 2.9416117668151855,
"score": 4.854694843292236
},
"weights_sha256": "0424555feea3126ee02d8d1b12636fad8cf491a5964a00a04b2fec67bcc0f602",
"profile": "dohnuts"
} |