Instructions to use QuantPasture/Step-3.5-Flash-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use QuantPasture/Step-3.5-Flash-GGUF 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 QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantPasture/Step-3.5-Flash-GGUF: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 QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantPasture/Step-3.5-Flash-GGUF: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 QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantPasture/Step-3.5-Flash-GGUF with Ollama:
```
ollama run hf.co/QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M
```
Unsloth Desktop

How to use QuantPasture/Step-3.5-Flash-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantPasture/Step-3.5-Flash-GGUF: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": "QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use QuantPasture/Step-3.5-Flash-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M
```

Lemonade

How to use QuantPasture/Step-3.5-Flash-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Step-3.5-Flash-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use QuantPasture/Step-3.5-Flash-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantPasture/Step-3.5-Flash-GGUF: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 QuantPasture/Step-3.5-Flash-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use QuantPasture/Step-3.5-Flash-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantPasture/Step-3.5-Flash-GGUF: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 "QuantPasture/Step-3.5-Flash-GGUF: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"

Quants With MTP

by tnhnyzc - opened Apr 8

Discussion

tnhnyzc

Apr 8

First of all, thanks a lot for the quants!

I've been able to load and run both IQ3_XXS and IQ4_XS on my hardware with actually good amount of ctx window (131k) and actually get decent decode speeds (15-16 tps - not fast by any means but ok) but more importantly, with some -ot tuning and --tensor-split, I'm able to get very decent pp speed (around 500 tps for a prompt size of 16K - opencode system prompt). The performance is much better than I expected for my hardware and the sizes are ideal, the quality also seems good.

I'm not sure if I can get more performance with MTP on my hardware and config I'm running but I wanted to try the https://github.com/stepfun-ai/llama.cpp/tree/step3p5-mtp with MTP but I realized these quants don't have the MTP heads. Would you consider uploading ones with MTP heads as well since the support also might merge into main llama.cpp soon?

AesSedai

Aes Sedai's Quant Pasture org Apr 11

If MTP gets merged into mainline llama.cpp, I'll requant it to support that.

SharkDiscord

May 16

Now that MTP has been merged into the main branch of llama.cpp, will this model be updated to support MTP?

AesSedai

Aes Sedai's Quant Pasture org May 16

Welp, guess I need to now 😂

I'll look into this in the next few days.

tnhnyzc

May 27

I have uploaded a few, in case anyone's interested in the meantime as options. Though I am looking forward to your updated quants AesSedai whenever you get the chance.

AesSedai

Aes Sedai's Quant Pasture org May 29

Coincidentally I've started converting the Step-3.7-Flash now, so I'll backfill this one too.

AesSedai

Aes Sedai's Quant Pasture org May 29

Actually I don't think the Step-Flash quants support MTP in llama.cpp yet: https://github.com/ggml-org/llama.cpp/pull/23274

The PR is probably close to merging, I've already got the 3.7 quants and will upload those. When MTP support merges, I'll re-quant.

AesSedai

Aes Sedai's Quant Pasture org Jun 2

I've uploaded updated 3.7-Flash quants, will be redoing the 3.5-Flash quants tonight or tomorrow.

tnhnyzc

Jun 3

@AesSedai , thanks a lot!

AesSedai

Aes Sedai's Quant Pasture org Jun 3

These Step-3.5-Flash quants have been updated with MTP now.

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