Instructions to use Verdugie/Fable-Therapy-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Verdugie/Fable-Therapy-4B 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 Verdugie/Fable-Therapy-4B:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Verdugie/Fable-Therapy-4B:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Verdugie/Fable-Therapy-4B:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Verdugie/Fable-Therapy-4B: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 Verdugie/Fable-Therapy-4B:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Verdugie/Fable-Therapy-4B: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 Verdugie/Fable-Therapy-4B:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Verdugie/Fable-Therapy-4B:Q4_K_M

Use Docker

docker model run hf.co/Verdugie/Fable-Therapy-4B:Q4_K_M

LM Studio
Jan

vLLM

How to use Verdugie/Fable-Therapy-4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Verdugie/Fable-Therapy-4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Verdugie/Fable-Therapy-4B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Verdugie/Fable-Therapy-4B:Q4_K_M

Ollama
How to use Verdugie/Fable-Therapy-4B with Ollama:
```
ollama run hf.co/Verdugie/Fable-Therapy-4B:Q4_K_M
```
Unsloth Desktop

How to use Verdugie/Fable-Therapy-4B with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Verdugie/Fable-Therapy-4B: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": "Verdugie/Fable-Therapy-4B:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Verdugie/Fable-Therapy-4B with Docker Model Runner:
```
docker model run hf.co/Verdugie/Fable-Therapy-4B:Q4_K_M
```

Lemonade

How to use Verdugie/Fable-Therapy-4B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Verdugie/Fable-Therapy-4B:Q4_K_M

Run and chat with the model

lemonade run user.Fable-Therapy-4B-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Verdugie/Fable-Therapy-4B with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Verdugie/Fable-Therapy-4B: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 Verdugie/Fable-Therapy-4B:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Verdugie/Fable-Therapy-4B with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Verdugie/Fable-Therapy-4B: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 "Verdugie/Fable-Therapy-4B: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"

Verdugie commited on Jun 27

Commit

c76aabd

verified ·

1 Parent(s): 9959e99

Unify training-conversation count with 9B (4,537)

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -23,7 +23,7 @@ pipeline_tag: text-generation
 ## Fable-Therapy-4B
-The compact sibling of [Fable-Therapy-9B](https://huggingface.co/Verdugie/Fable-Therapy-9B) — a therapy-style conversational model fine-tuned from Qwen 3.5 4B on **4,534 counseling conversations whose clinical reasoning was reverse-engineered from Claude Fable 5 by Claude Opus 4.8**. Same lineage, same disposition-in-the-weights philosophy, same structured reasoning trace — at a surface area small enough to run on a phone, integrated graphics, or a low-VRAM card, entirely on your own hardware.
 Where Opus-Therapy distilled Claude Opus end to end, Fable-Therapy derives its clinical *reasoning* and its *prose* from **Claude Fable 5** — the strongest clinical reasoner in the family — reconstructed for open weights by Opus 4.8, and re-instrumented with an experimental reasoning trace that is this model's own. The 4B carries that methodology at a smaller scale: it reasons before it speaks and holds a timeline ledger, with the trade-offs you'd expect from a 4B (see **Versatility Battery** and **Limitations**).
@@ -86,7 +86,7 @@ It is not a replacement for a therapist, and not a crisis service. See **Limitat
 | Attribute | Value |
 |-----------|-------|
 | **Base Model** | Qwen 3.5 4B (hybrid GatedDeltaNet + attention), text-only |
-| **Training Data** | 4,534 therapy conversations — Fable-5-derived clinical reasoning and prose, reconstructed by Opus 4.8 |
 | **Fine-tune Method** | QLoRA (4-bit, r=32, α=64), 7-target (q/k/v/o/gate/up/down), via Unsloth + TRL |
 | **Training Hardware** | NVIDIA RTX 4090 24GB (local) |
 | **Precision** | bf16 compute / 4-bit base |

 ## Fable-Therapy-4B
+The compact sibling of [Fable-Therapy-9B](https://huggingface.co/Verdugie/Fable-Therapy-9B) — a therapy-style conversational model fine-tuned from Qwen 3.5 4B on **4,537 counseling conversations whose clinical reasoning was reverse-engineered from Claude Fable 5 by Claude Opus 4.8**. Same lineage, same disposition-in-the-weights philosophy, same structured reasoning trace — at a surface area small enough to run on a phone, integrated graphics, or a low-VRAM card, entirely on your own hardware.
 Where Opus-Therapy distilled Claude Opus end to end, Fable-Therapy derives its clinical *reasoning* and its *prose* from **Claude Fable 5** — the strongest clinical reasoner in the family — reconstructed for open weights by Opus 4.8, and re-instrumented with an experimental reasoning trace that is this model's own. The 4B carries that methodology at a smaller scale: it reasons before it speaks and holds a timeline ledger, with the trade-offs you'd expect from a 4B (see **Versatility Battery** and **Limitations**).
 | Attribute | Value |
 |-----------|-------|
 | **Base Model** | Qwen 3.5 4B (hybrid GatedDeltaNet + attention), text-only |
+| **Training Data** | 4,537 therapy conversations — Fable-5-derived clinical reasoning and prose, reconstructed by Opus 4.8 |
 | **Fine-tune Method** | QLoRA (4-bit, r=32, α=64), 7-target (q/k/v/o/gate/up/down), via Unsloth + TRL |
 | **Training Hardware** | NVIDIA RTX 4090 24GB (local) |
 | **Precision** | bf16 compute / 4-bit base |