Instructions to use fableforge-ai/FableForge-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fableforge-ai/FableForge-1.5B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="fableforge-ai/FableForge-1.5B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("fableforge-ai/FableForge-1.5B")
model = AutoModelForCausalLM.from_pretrained("fableforge-ai/FableForge-1.5B")

llama-cpp-python

How to use fableforge-ai/FableForge-1.5B with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="fableforge-ai/FableForge-1.5B",
	filename="fableforge-1.5b-f16.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use fableforge-ai/FableForge-1.5B 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 fableforge-ai/FableForge-1.5B:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf fableforge-ai/FableForge-1.5B:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf fableforge-ai/FableForge-1.5B:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf fableforge-ai/FableForge-1.5B: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 fableforge-ai/FableForge-1.5B:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf fableforge-ai/FableForge-1.5B: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 fableforge-ai/FableForge-1.5B:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf fableforge-ai/FableForge-1.5B:Q4_K_M

Use Docker

docker model run hf.co/fableforge-ai/FableForge-1.5B:Q4_K_M

LM Studio
Jan

vLLM

How to use fableforge-ai/FableForge-1.5B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fableforge-ai/FableForge-1.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fableforge-ai/FableForge-1.5B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/fableforge-ai/FableForge-1.5B:Q4_K_M

SGLang

How to use fableforge-ai/FableForge-1.5B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "fableforge-ai/FableForge-1.5B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fableforge-ai/FableForge-1.5B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "fableforge-ai/FableForge-1.5B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fableforge-ai/FableForge-1.5B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use fableforge-ai/FableForge-1.5B with Ollama:
```
ollama run hf.co/fableforge-ai/FableForge-1.5B:Q4_K_M
```

Unsloth Studio

How to use fableforge-ai/FableForge-1.5B 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 fableforge-ai/FableForge-1.5B 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 fableforge-ai/FableForge-1.5B to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for fableforge-ai/FableForge-1.5B to start chatting

Atomic Chat new
Docker Model Runner
How to use fableforge-ai/FableForge-1.5B with Docker Model Runner:
```
docker model run hf.co/fableforge-ai/FableForge-1.5B:Q4_K_M
```

Lemonade

How to use fableforge-ai/FableForge-1.5B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull fableforge-ai/FableForge-1.5B:Q4_K_M

Run and chat with the model

lemonade run user.FableForge-1.5B-Q4_K_M

List all available models

lemonade list

FableForge-1.5B / README.md

King3Djbl

Viral card: model-tree metadata, quant table, Ollama-from-source, demo funnel

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	---
	license: apache-2.0
	language:
	- en
	library_name: transformers
	pipeline_tag: text-generation
	base_model: Qwen/Qwen2.5-1.5B-Instruct
	base_model_relation: finetune
	tags:
	- coding
	- fableforge
	- generalist
	- gguf
	- imatrix
	- llama.cpp
	- lm-studio
	- nexus
	- ollama
	- reasoning
	- text-generation
	- uncensored
	---

	# FableForge-1.5B

	> FableForge generalist — all NEXUS domains distilled into one model.

	[![Downloads](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fhuggingface.co%2Fapi%2Fmodels%2Ffableforge-ai%2FFableForge-1.5B&query=downloads&label=downloads&color=blue)](https://huggingface.co/fableforge-ai/FableForge-1.5B) [![Demos](https://img.shields.io/badge/🤗-Live%20Demos-orange)](https://huggingface.co/spaces/fableforge-ai/fableforge-nexus)

	Base model: [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) · Part of the FableForge ecosystem.

	---

	## ⚡ Quickest start — Ollama (pulls straight from this repo → credits the source)

	```bash
	ollama run hf.co/fableforge-ai/FableForge-1.5B:Q4_K_M
	```

	## 🦙 llama.cpp

	```bash
	llama-cli -hf fableforge-ai/FableForge-1.5B:Q4_K_M -p "Hello!"
	```

	## 💠 LM Studio
	Search `fableforge-ai/FableForge-1.5B` and pick a quant below.

	---

	## 📦 Provided quants (download one file, not the whole repo)

	\| File \| Quant \| Size \| Notes \|
	\| ---- \| ----- \| ---- \| ----- \|
	\| [fableforge-1.5b-f16.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-f16.gguf) \| `F16` \| 3.09 GB \| Full precision (unquantized). Reference / conversion. \|
	\| [fableforge-1.5b-q8_0.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-q8_0.gguf) \| `Q8_0` \| 1.65 GB \| Extremely high quality — usually overkill. \|
	\| [fableforge-1.5b-q6_k.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-q6_k.gguf) \| `Q6_K` \| 1.27 GB \| Very high quality, near-perfect. Recommended if you have the RAM. \|
	\| [fableforge-1.5b-q5_k_m.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-q5_k_m.gguf) \| `Q5_K_M` \| 1.13 GB \| High quality. Recommended. \|
	\| [fableforge-1.5b-q4_k_m.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-q4_k_m.gguf) \| `Q4_K_M` \| 0.99 GB \| ⭐ Best size/quality balance — default pick for most users. \|
	\| [fableforge-1.5b-iq4_xs.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-iq4_xs.gguf) \| `IQ4_XS` \| 0.90 GB \| imatrix — great quality, smaller than Q4_K_S. Recommended for low RAM. \|
	\| [fableforge-1.5b-q4_0.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-q4_0.gguf) \| `Q4_0` \| 0.93 GB \| Legacy format — prefer Q4_K_M. \|
	\| [fableforge-1.5b-q3_k_m.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-q3_k_m.gguf) \| `Q3_K_M` \| 0.82 GB \| Lower quality; usable when RAM is tight. \|
	\| [fableforge-1.5b-iq3_xxs.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-iq3_xxs.gguf) \| `IQ3_XXS` \| 0.67 GB \| imatrix very low quality. \|
	\| [fableforge-1.5b-q2_k.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-q2_k.gguf) \| `Q2_K` \| 0.68 GB \| Very low quality — surprisingly usable. \|
	\| [fableforge-1.5b-iq2_xxs.gguf](https://huggingface.co/fableforge-ai/FableForge-1.5B/blob/main/fableforge-1.5b-iq2_xxs.gguf) \| `IQ2_XXS` \| 0.51 GB \| Tiny imatrix — last resort. \|

	Not sure? Take `Q4_K_M`. Low RAM → `IQ4_XS`. Max quality → `Q6_K`.

	## 🧠 Prompt format (ChatML)

	```
	<\|im_start\|>system
	{system_prompt}<\|im_end\|>
	<\|im_start\|>user
	{prompt}<\|im_end\|>
	<\|im_start\|>assistant
	```

	## 🌌 See it live — the FableForge demos

	This family powers a galaxy of free, interactive HF Spaces:

	- 🧭 [FableForge Nexus](https://huggingface.co/spaces/fableforge-ai/fableforge-nexus)
	- 🍺 [Infinite NPC](https://huggingface.co/spaces/fableforge-ai/infinite-npc)
	- 🎭 [Dual-GM](https://huggingface.co/spaces/King3Djbl/dual-gm-simulator)
	- 💻 [ShellWhisperer](https://huggingface.co/spaces/King3Djbl/shellwhisperer-terminal)
	- 👻 [Ghost Writer](https://huggingface.co/spaces/fableforge-ai/ghost-writer)

	---

	⭐ Like & share — it helps people find the source instead of a mirror.