Instructions to use datacrunch/tolkio-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use datacrunch/tolkio-models 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 datacrunch/tolkio-models
# Run inference directly in the terminal:
llama cli -hf datacrunch/tolkio-models

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf datacrunch/tolkio-models
# Run inference directly in the terminal:
llama cli -hf datacrunch/tolkio-models

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 datacrunch/tolkio-models
# Run inference directly in the terminal:
./build/bin/llama cli -hf datacrunch/tolkio-models

Use Docker

docker model run hf.co/datacrunch/tolkio-models

Llama new
LM Studio
Jan
Ollama
How to use datacrunch/tolkio-models with Ollama:
```
ollama run hf.co/datacrunch/tolkio-models
```
Unsloth Desktop

How to use datacrunch/tolkio-models with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf datacrunch/tolkio-models

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": "datacrunch/tolkio-models"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use datacrunch/tolkio-models with Docker Model Runner:
```
docker model run hf.co/datacrunch/tolkio-models
```

Lemonade

How to use datacrunch/tolkio-models with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull datacrunch/tolkio-models

Run and chat with the model

lemonade run user.tolkio-models-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use datacrunch/tolkio-models with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf datacrunch/tolkio-models

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 datacrunch/tolkio-models

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use datacrunch/tolkio-models with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf datacrunch/tolkio-models

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 "datacrunch/tolkio-models" \
  --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"

datacrunch commited on 13 days ago

Commit

9e65491

verified ·

1 Parent(s): e346b3f

Spoken language classifier (Silero, MIT) with the Asian and African packs

Browse files

Files changed (1) hide show

models.json +20 -0

models.json CHANGED Viewed

@@ -260,6 +260,11 @@
      "path": "voices/nd/voice.json",
      "size": 834,
      "sha256": "c79672cf3eb54449a09a2ac2f591a27368b8de29dc60ed7f6cbb5e0de93894f5"
     }
    ]
   },
@@ -298,6 +303,11 @@
      "path": "asia/ja/asr/tokens.txt",
      "size": 28557,
      "sha256": "732f64c53909f2620c713f4106b487d92e6f54a6915b3cd3d1dbd32f9f4f392a"
     }
    ]
   },
@@ -352,6 +362,11 @@
      "path": "asia/zh/voice/lexicon-zh.txt",
      "size": 2119465,
      "sha256": "11111d8cd695fba2ace1367a1d0a708b586e6ef5c1f9be91da5d7eef129b651c"
     }
    ]
   },
@@ -371,6 +386,11 @@
      "path": "africa/asr/tokens.txt",
      "size": 90630,
      "sha256": "7d99997ef207ff14c2cfe825f2aa037528ea250113cc3c6392bfe49326884ba6"
     }
    ]
   }

      "path": "voices/nd/voice.json",
      "size": 834,
      "sha256": "c79672cf3eb54449a09a2ac2f591a27368b8de29dc60ed7f6cbb5e0de93894f5"
+    },
+    {
+     "path": "lid/lang95.onnx",
+     "size": 16972591,
+     "sha256": "12a91f706ad6ca5a5eba4e84a96739d077e56f121ec71db86a752f62e218a227"
     }
    ]
   },
      "path": "asia/ja/asr/tokens.txt",
      "size": 28557,
      "sha256": "732f64c53909f2620c713f4106b487d92e6f54a6915b3cd3d1dbd32f9f4f392a"
+    },
+    {
+     "path": "lid/lang95.onnx",
+     "size": 16972591,
+     "sha256": "12a91f706ad6ca5a5eba4e84a96739d077e56f121ec71db86a752f62e218a227"
     }
    ]
   },
      "path": "asia/zh/voice/lexicon-zh.txt",
      "size": 2119465,
      "sha256": "11111d8cd695fba2ace1367a1d0a708b586e6ef5c1f9be91da5d7eef129b651c"
+    },
+    {
+     "path": "lid/lang95.onnx",
+     "size": 16972591,
+     "sha256": "12a91f706ad6ca5a5eba4e84a96739d077e56f121ec71db86a752f62e218a227"
     }
    ]
   },
      "path": "africa/asr/tokens.txt",
      "size": 90630,
      "sha256": "7d99997ef207ff14c2cfe825f2aa037528ea250113cc3c6392bfe49326884ba6"
+    },
+    {
+     "path": "lid/lang95.onnx",
+     "size": 16972591,
+     "sha256": "12a91f706ad6ca5a5eba4e84a96739d077e56f121ec71db86a752f62e218a227"
     }
    ]
   }