Instructions to use talxcc/Tals-coder-flash-02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use talxcc/Tals-coder-flash-02 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 talxcc/Tals-coder-flash-02
# Run inference directly in the terminal:
llama cli -hf talxcc/Tals-coder-flash-02

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf talxcc/Tals-coder-flash-02
# Run inference directly in the terminal:
llama cli -hf talxcc/Tals-coder-flash-02

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 talxcc/Tals-coder-flash-02
# Run inference directly in the terminal:
./build/bin/llama cli -hf talxcc/Tals-coder-flash-02

Use Docker

docker model run hf.co/talxcc/Tals-coder-flash-02

Llama new
LM Studio
Jan

vLLM

How to use talxcc/Tals-coder-flash-02 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "talxcc/Tals-coder-flash-02"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "talxcc/Tals-coder-flash-02",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/talxcc/Tals-coder-flash-02

Ollama
How to use talxcc/Tals-coder-flash-02 with Ollama:
```
ollama run hf.co/talxcc/Tals-coder-flash-02
```
Unsloth Desktop

How to use talxcc/Tals-coder-flash-02 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf talxcc/Tals-coder-flash-02

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": "talxcc/Tals-coder-flash-02"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use talxcc/Tals-coder-flash-02 with Docker Model Runner:
```
docker model run hf.co/talxcc/Tals-coder-flash-02
```

Lemonade

How to use talxcc/Tals-coder-flash-02 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull talxcc/Tals-coder-flash-02

Run and chat with the model

lemonade run user.Tals-coder-flash-02-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use talxcc/Tals-coder-flash-02 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf talxcc/Tals-coder-flash-02

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 talxcc/Tals-coder-flash-02

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use talxcc/Tals-coder-flash-02 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf talxcc/Tals-coder-flash-02

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 "talxcc/Tals-coder-flash-02" \
  --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"

talxcc commited on Oct 1

Commit

4e405ec

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1 Parent(s): 3964958

Update README.md

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README.md +2 -4

README.md CHANGED Viewed

@@ -31,12 +31,10 @@ pipeline_tag: text-generation
 ### *"Why wait 5 minutes for a reasoning model to finish an existential crisis in its chain-of-thought? Tals-coder-flash-02 goes at lightning speed with 60 tok/s on a budget 16GB GPU."*
-<p align="left">
   <img src="proof.gif" width="300" height="300" alt="The Flash Lightning Speed" />
-   align="right">
-  <img src="metrics.gif" width="300" height="300" alt="The Flash Lightning Speed" />
 </p>
-<p align="right">
   <img src="metrics.gif" width="300" height="300" alt="The Flash Lightning Speed" />
 </p>
 </div>

 ### *"Why wait 5 minutes for a reasoning model to finish an existential crisis in its chain-of-thought? Tals-coder-flash-02 goes at lightning speed with 60 tok/s on a budget 16GB GPU."*
+<p align="center">
   <img src="proof.gif" width="300" height="300" alt="The Flash Lightning Speed" />
 </p>
+<p align="center">
   <img src="metrics.gif" width="300" height="300" alt="The Flash Lightning Speed" />
 </p>
 </div>