PEFT
Safetensors
GGUF
Russian
English
lora
qwen3
tool-use
function-calling
router
russian
conversational
Instructions to use digitable-lol/digit-router-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use digitable-lol/digit-router-0.6b with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use digitable-lol/digit-router-0.6b 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 digitable-lol/digit-router-0.6b:Q4_K_M # Run inference directly in the terminal: llama cli -hf digitable-lol/digit-router-0.6b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf digitable-lol/digit-router-0.6b:Q4_K_M # Run inference directly in the terminal: llama cli -hf digitable-lol/digit-router-0.6b: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 digitable-lol/digit-router-0.6b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf digitable-lol/digit-router-0.6b: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 digitable-lol/digit-router-0.6b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf digitable-lol/digit-router-0.6b:Q4_K_M
Use Docker
docker model run hf.co/digitable-lol/digit-router-0.6b:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use digitable-lol/digit-router-0.6b with Ollama:
ollama run hf.co/digitable-lol/digit-router-0.6b:Q4_K_M
- Unsloth Studio
How to use digitable-lol/digit-router-0.6b with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for digitable-lol/digit-router-0.6b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for digitable-lol/digit-router-0.6b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for digitable-lol/digit-router-0.6b to start chatting
- Pi
How to use digitable-lol/digit-router-0.6b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf digitable-lol/digit-router-0.6b:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "digitable-lol/digit-router-0.6b:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use digitable-lol/digit-router-0.6b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf digitable-lol/digit-router-0.6b: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 "digitable-lol/digit-router-0.6b: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"
- Docker Model Runner
How to use digitable-lol/digit-router-0.6b with Docker Model Runner:
docker model run hf.co/digitable-lol/digit-router-0.6b:Q4_K_M
- Lemonade
How to use digitable-lol/digit-router-0.6b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull digitable-lol/digit-router-0.6b:Q4_K_M
Run and chat with the model
lemonade run user.digit-router-0.6b-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use digitable-lol/digit-router-0.6b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf digitable-lol/digit-router-0.6b: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 digitable-lol/digit-router-0.6b:Q4_K_M
Run Hermes
hermes
- Atomic Chat
| { | |
| "generated_at": "2026-08-04T00:37:22+00:00", | |
| "repo_id": "digitable-lol/digit-router-0.6b", | |
| "note": "sha256 of every file as published. The hash is the record, not the filename: a repository is the same artefact as this manifest only if every digest matches.", | |
| "files": [ | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/adapter_config.json", | |
| "sha256": "0cf52cd46c2b93a2c7858c03f13542bea01764a6b5f9ae7ab6810c039c1f949c", | |
| "size_bytes": 1148 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/adapter_model.safetensors", | |
| "sha256": "c71e525b3db16bb2932d4e53369fb912f4ef4d990def9c248aa60091e0af061f", | |
| "size_bytes": 80792456 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/tokenizer.json", | |
| "sha256": "be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506", | |
| "size_bytes": 11422650 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/tokenizer_config.json", | |
| "sha256": "04b1682c59acbd057f4c9072297faa73d56fc9de053094c659cdb4c464f58f86", | |
| "size_bytes": 694 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/chat_template.jinja", | |
| "sha256": "a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8", | |
| "size_bytes": 4168 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/training_args.bin", | |
| "sha256": "b286de5b87e45efc28eae1e79bbd82a86228a03f84303bb3614d7f092a45fbea", | |
| "size_bytes": 5777 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/train_summary.json", | |
| "sha256": "162b9908a1f661a884c736e4948b10b5ff763a86b4d5bc7ef1ec477a0411e865", | |
| "size_bytes": 514 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/log_history.json", | |
| "sha256": "08b3e175fe37da7f0fab6b6b46afcf4256abaab09e6a2c5babd15aa5948fc071", | |
| "size_bytes": 25938 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-lora/README.md", | |
| "sha256": "c21c21179d4ef5bfe1e1411f73f539f7c66c304b0dd169ad14ec3913e32866a8", | |
| "size_bytes": 1450 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/adapter_config.json", | |
| "sha256": "3502d36a221f480c76df204b51e310f7d791f37fba6c4e3bba228e5612fb756e", | |
| "size_bytes": 1148 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/adapter_model.safetensors", | |
| "sha256": "7816f7576c6a118c4785045ea8d2dc5ab766d7a63e1c1937330022aede6b4a22", | |
| "size_bytes": 80792456 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/tokenizer.json", | |
| "sha256": "be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506", | |
| "size_bytes": 11422650 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/tokenizer_config.json", | |
| "sha256": "04b1682c59acbd057f4c9072297faa73d56fc9de053094c659cdb4c464f58f86", | |
| "size_bytes": 694 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/chat_template.jinja", | |
| "sha256": "a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8", | |
| "size_bytes": 4168 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/training_args.bin", | |
| "sha256": "424966306d51739e9befd3219013f6087bf7aba133354b71ecf7de99401d11db", | |
| "size_bytes": 5777 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/train_summary.json", | |
| "sha256": "96deacf4adb9c417515d12fc260e82c61d8af55e523ec25bdc487ca7afe68149", | |
| "size_bytes": 557 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/log_history.json", | |
| "sha256": "3aec356139ac8598962adbc2ca0ae33a479a2a97152c7dcd193ff6f4b7fc19da", | |
| "size_bytes": 27106 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v2-lora/README.md", | |
| "sha256": "c848e539490712ad00e4331a0793f92e28c5b4eaf78346bd2eb2ff7ef8f0bafe", | |
| "size_bytes": 1456 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/adapter_config.json", | |
| "sha256": "f79f2bb062f4c429bf720b03a96b355102f12954af1c4e2857e626e0695d9d01", | |
| "size_bytes": 1148 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/adapter_model.safetensors", | |
| "sha256": "ffb30c78a64c5aadf7d4426494ba507f4d1ea9b4f19980fe35d0ac488abe4316", | |
| "size_bytes": 80792456 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/tokenizer.json", | |
| "sha256": "be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506", | |
| "size_bytes": 11422650 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/tokenizer_config.json", | |
| "sha256": "04b1682c59acbd057f4c9072297faa73d56fc9de053094c659cdb4c464f58f86", | |
| "size_bytes": 694 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/chat_template.jinja", | |
| "sha256": "a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8", | |
| "size_bytes": 4168 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/training_args.bin", | |
| "sha256": "9c45a7f62d2baf7fa3b866b26dc50e08b943003dfa300d6235ae3f7182a6beff", | |
| "size_bytes": 5777 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/train_summary.json", | |
| "sha256": "dc6e5fd79c33c399344c78f362f8da90ef575a438dde6c8538a517526caf33cd", | |
| "size_bytes": 556 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/log_history.json", | |
| "sha256": "309c2c82efe8f513befa44f48e1958634d78e26eabfe60f661404f96b068c25e", | |
| "size_bytes": 27389 | |
| }, | |
| { | |
| "path_in_repo": "adapters/router-0.6b-v3-lora/README.md", | |
| "sha256": "3ead20c884fb9087c275e36037342933fe8a47ec326a2b19105b6fdd7cfc89c9", | |
| "size_bytes": 1456 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v2-F16.gguf", | |
| "sha256": "0c0d4c448cf656c7aeeb6cf333ea7bc8673d9a5b5d2c59ffde03f852b076233d", | |
| "size_bytes": 1198182176 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v2-Q8_0.gguf", | |
| "sha256": "a63016509e04ed05f753c49518da46a7e460fbc02a6ddf1b426294a2dfcba94a", | |
| "size_bytes": 639446816 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v2-Q5_K_M.gguf", | |
| "sha256": "c88bc0b8ca9a740b5df0d15fb0b01a108a6a951879d47dc63b018adc25a4f11e", | |
| "size_bytes": 444414752 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v2-Q4_K_M.gguf", | |
| "sha256": "a06886a35fd8b6450a8df6cd5f9ba1079dbfecd3d12a44d3c8775c108a8870e8", | |
| "size_bytes": 396704544 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v2-Q4_K_M-imat.gguf", | |
| "sha256": "f0b2ac781809f314e85ce574742955a3cb481efc158aaff469e455645919abb4", | |
| "size_bytes": 396704800 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v2.imatrix", | |
| "sha256": "27cccd29fb5f4f16ed095b5dd79179504e62c952700186c49a902040d12e1de4", | |
| "size_bytes": 1177056 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v3-F16.gguf", | |
| "sha256": "5ebbc03044d4749521fae78febad9a81786decfd41da1c4e7573eea23e6cc57d", | |
| "size_bytes": 1198182176 | |
| }, | |
| { | |
| "path_in_repo": "gguf/router-0.6b-v3-Q5_K_M.gguf", | |
| "sha256": "1621643b05ba0748a6747c664ebca637cb5049857d7dc6464d96d104d5d90e5a", | |
| "size_bytes": 444414752 | |
| }, | |
| { | |
| "path_in_repo": "README.md", | |
| "sha256": "ad7f9d89912f52759df45ef8bad17b804cafe0c5c74f49ca921622222eb39b1a", | |
| "size_bytes": 27794 | |
| } | |
| ] | |
| } | |