Instructions to use tchbcb/samai-8b-M8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use tchbcb/samai-8b-M8 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 tchbcb/samai-8b-M8:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf tchbcb/samai-8b-M8:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf tchbcb/samai-8b-M8:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf tchbcb/samai-8b-M8: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 tchbcb/samai-8b-M8:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf tchbcb/samai-8b-M8: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 tchbcb/samai-8b-M8:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tchbcb/samai-8b-M8:Q4_K_M

Use Docker

docker model run hf.co/tchbcb/samai-8b-M8:Q4_K_M

Llama new
LM Studio
Jan
Ollama
How to use tchbcb/samai-8b-M8 with Ollama:
```
ollama run hf.co/tchbcb/samai-8b-M8:Q4_K_M
```
Unsloth Desktop

How to use tchbcb/samai-8b-M8 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tchbcb/samai-8b-M8: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": "tchbcb/samai-8b-M8:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use tchbcb/samai-8b-M8 with Docker Model Runner:
```
docker model run hf.co/tchbcb/samai-8b-M8:Q4_K_M
```

Lemonade

How to use tchbcb/samai-8b-M8 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tchbcb/samai-8b-M8:Q4_K_M

Run and chat with the model

lemonade run user.samai-8b-M8-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use tchbcb/samai-8b-M8 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tchbcb/samai-8b-M8: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 tchbcb/samai-8b-M8:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use tchbcb/samai-8b-M8 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tchbcb/samai-8b-M8: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 "tchbcb/samai-8b-M8: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"

tchbcb commited on Sep 24

Commit

cf8d8e3

verified ·

1 Parent(s): 4a24dbe

r13 v2 final: r13_ship.py (all patches baked)

Browse files

Files changed (1) hide show

artifacts/r13_scripts/r13_ship.py +2 -2

artifacts/r13_scripts/r13_ship.py CHANGED Viewed

@@ -89,7 +89,7 @@ def s9_serve():
     FIN = K8B + "/m13_r10_gsqrco_v1.gguf"
     MMP = K8B + "/mmproj_m11.gguf"
     sh("pkill -f llama-server; sleep 3", 60)
-    cmd = ("nohup %s %s/llama-server -m %s --mmproj %s --host 0.0.0.0 --port 8101 "
            "--api-key 1234 -c 131072 -fa on -ctk q8_0 -ctv q8_0 -t 2 -ngl 99 "
            "> /tmp/k8b/serve_r13.log 2>&1 &" % (LC_ENV, LCF, FIN, MMP))
     open(K8B + "/R13_SERVE_CMD_NEW", "w").write(
@@ -121,7 +121,7 @@ def fallback_serving_old():
         return
     if subprocess.run("ps ax | grep '[l]lama-server' | head -1", shell=True, capture_output=True, text=True).stdout.strip():
         return
-    cmd = ("nohup %s %s/llama-server -m %s --mmproj %s --host 0.0.0.0 --port 8101 "
            "--api-key 1234 -c 131072 -fa on -ctk q8_0 -ctv q8_0 -t 2 -ngl 99 "
            "> /tmp/k8b/serve_old_fallback.log 2>&1 &" % (LC_ENV, LCF, OLD, MMP))
     sh(cmd, 30)

     FIN = K8B + "/m13_r10_gsqrco_v1.gguf"
     MMP = K8B + "/mmproj_m11.gguf"
     sh("pkill -f llama-server; sleep 3", 60)
+    cmd = ("%s nohup %s/llama-server -m %s --mmproj %s --host 0.0.0.0 --port 8101 "
            "--api-key 1234 -c 131072 -fa on -ctk q8_0 -ctv q8_0 -t 2 -ngl 99 "
            "> /tmp/k8b/serve_r13.log 2>&1 &" % (LC_ENV, LCF, FIN, MMP))
     open(K8B + "/R13_SERVE_CMD_NEW", "w").write(
         return
     if subprocess.run("ps ax | grep '[l]lama-server' | head -1", shell=True, capture_output=True, text=True).stdout.strip():
         return
+    cmd = ("%s nohup %s/llama-server -m %s --mmproj %s --host 0.0.0.0 --port 8101 "
            "--api-key 1234 -c 131072 -fa on -ctk q8_0 -ctv q8_0 -t 2 -ngl 99 "
            "> /tmp/k8b/serve_old_fallback.log 2>&1 &" % (LC_ENV, LCF, OLD, MMP))
     sh(cmd, 30)