Instructions to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus 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 jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus
# Run inference directly in the terminal:
llama cli -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus
# Run inference directly in the terminal:
llama cli -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

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 jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus
# Run inference directly in the terminal:
./llama-cli -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

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 jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus
# Run inference directly in the terminal:
./build/bin/llama-cli -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

Use Docker

docker model run hf.co/jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

LM Studio
Jan

vLLM

How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

Ollama
How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with Ollama:
```
ollama run hf.co/jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus
```

Unsloth Studio

How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus 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 jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus 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 jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus to start chatting

How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

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": "jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with Docker Model Runner:
```
docker model run hf.co/jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus
```

Lemonade

How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

Run and chat with the model

lemonade run user.Step-3.7-Flash-ROCmFPX-Q3-QualityPlus-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

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 jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus

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 "jcbtc/Step-3.7-Flash-ROCmFPX-Q3-QualityPlus" \
  --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"

jcbtc commited on Jul 19

Commit

9fe990f

verified ·

1 Parent(s): fa311ca

Add model card

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README.md +11 -3

README.md CHANGED Viewed

@@ -196,11 +196,19 @@ Use the pinned Ciru runner:
 ```text
 repo: https://github.com/ciru-ai/ROCmFPX
-current recommended pin: 221402af8574faf652b101b6afe225a3f329561f
 branch at time of pin: main
 upstream lineage: charlie12345/ROCmFPX
 ```
 The earlier Chadrock v2 speed-runner tag remains useful for historical comparison:
 ```text
@@ -219,7 +227,7 @@ distros.
 ```bash
 git clone https://github.com/ciru-ai/ROCmFPX.git
 cd ROCmFPX
-git checkout 221402af8574faf652b101b6afe225a3f329561f
 env JOBS="$(nproc)" \
   CMAKE_HIP_ARCHITECTURES=gfx1151 \
@@ -372,7 +380,7 @@ Converter-reported size: `83726.08 MiB / 3.57 BPW`, 9 shards.
 - Base model: [`stepfun-ai/Step-3.7-Flash`](https://huggingface.co/stepfun-ai/Step-3.7-Flash)
 - MTP draft GGUF source: [`notSnix/Step-3.7-Flash-MTP-Draft-GGUF`](https://huggingface.co/notSnix/Step-3.7-Flash-MTP-Draft-GGUF)
 - ROCmFPX creator: Charlie, `charlie12345` / `@italianclownz`, [`charlie12345/ROCmFPX`](https://github.com/charlie12345/ROCmFPX)
-- Pinned public runner fork and build recipe: [`ciru-ai/ROCmFPX`](https://github.com/ciru-ai/ROCmFPX), current recommended pin `221402af8574faf652b101b6afe225a3f329561f`
 - Quantization, the ROCmFPX Step 3.7 Q3 QualityPlus recipe, Strix Halo profile, and local benchmark work: Crown / Ciru
 ## Caveats

 ```text
 repo: https://github.com/ciru-ai/ROCmFPX
+current recommended pin: c14872f8407f5b0642f3c395439b929021df753a
 branch at time of pin: main
 upstream lineage: charlie12345/ROCmFPX
 ```
+This pin includes the upstream StepFun pre-render whitespace fix from
+[`ggml-org/llama.cpp@2d97363`](https://github.com/ggml-org/llama.cpp/commit/2d973636e292ee6f75fadcf08d29cb33511f509f).
+It trims accumulated whitespace from prior content, reasoning, and typed text
+parts before the Step template is rendered, preventing the progressive
+`Let me ... Actually ... Wait ...` reasoning loops seen in long multi-turn tool
+sessions. Keep using the downloadable fixed template below; the runner-side fix
+also protects clients that fall back to the GGUF's embedded Step template.
 The earlier Chadrock v2 speed-runner tag remains useful for historical comparison:
 ```text
 ```bash
 git clone https://github.com/ciru-ai/ROCmFPX.git
 cd ROCmFPX
+git checkout c14872f8407f5b0642f3c395439b929021df753a
 env JOBS="$(nproc)" \
   CMAKE_HIP_ARCHITECTURES=gfx1151 \
 - Base model: [`stepfun-ai/Step-3.7-Flash`](https://huggingface.co/stepfun-ai/Step-3.7-Flash)
 - MTP draft GGUF source: [`notSnix/Step-3.7-Flash-MTP-Draft-GGUF`](https://huggingface.co/notSnix/Step-3.7-Flash-MTP-Draft-GGUF)
 - ROCmFPX creator: Charlie, `charlie12345` / `@italianclownz`, [`charlie12345/ROCmFPX`](https://github.com/charlie12345/ROCmFPX)
+- Pinned public runner fork and build recipe: [`ciru-ai/ROCmFPX`](https://github.com/ciru-ai/ROCmFPX), current recommended pin `c14872f8407f5b0642f3c395439b929021df753a`
 - Quantization, the ROCmFPX Step 3.7 Q3 QualityPlus recipe, Strix Halo profile, and local benchmark work: Crown / Ciru
 ## Caveats