Instructions to use SL-AI/GRaPE-Mini-Writer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SL-AI/GRaPE-Mini-Writer with Transformers:

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

pipe = pipeline("text-generation", model="SL-AI/GRaPE-Mini-Writer")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("SL-AI/GRaPE-Mini-Writer")
model = AutoModelForMultimodalLM.from_pretrained("SL-AI/GRaPE-Mini-Writer", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SL-AI/GRaPE-Mini-Writer with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/SL-AI/GRaPE-Mini-Writer

SGLang

How to use SL-AI/GRaPE-Mini-Writer 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 "SL-AI/GRaPE-Mini-Writer" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SL-AI/GRaPE-Mini-Writer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "SL-AI/GRaPE-Mini-Writer" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SL-AI/GRaPE-Mini-Writer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use SL-AI/GRaPE-Mini-Writer with Docker Model Runner:
```
docker model run hf.co/SL-AI/GRaPE-Mini-Writer
```

GRaPE-Mini-Writer

File size: 1,827 Bytes

6c970b1

---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
library_name: transformers
---

![GRaPE_Logo](https://cdn-uploads.huggingface.co/production/uploads/66960602f0ffd8e3a381106a/XjHkzctrE41e1qqJYeDzN.png)

_The **G**eneral **R**easoning **A**gent (for) **P**roject **E**xploration_

# The Model
| Attribute | Size | Modalities | Domain |
| :--- | :--- | :--- | :--- |
| **GRaPE Mini Writer** | 3B | Text + Image + Video in, Text out | Creative Writing Tasks |

***

# Capabilities

GRaPE Mini Writer was created for creative writing tasks, being more powerful than GRaPE Mini

> *Note: GRaPE Mini Writer doesn't think before responding*

***

# How to Run

I recommend using **LM Studio** for running GRaPE Models, and have generally found these sampling parameters to work best:

| Name | Value |
| :--- | :--- | 
| **Temperature** | 0.6 |
| **Top K Sampling** | 40 |
| **Repeat Penalty** | 1 |
| **Top P Sampling** | 0.85 |
| **Min P Sampling** | 0.05 |

***

# GRaPE Mini Writer as a Model

GRaPE Mini Writer was a model planned to be used as an expert in a "GRaPE Pro 1" model, which was eventually scrapped due to the aging architecture, riskiness of model upcycling, and the innsufficient compute that SLAI has to train it.

***

# Architecture

* GRaPE Mini Writer: Built on the GRaPE Mini's architecture

***

# Notes

The GRaPE Family started all the way back in August of 2025, meaning these models are severely out of date on architecture, and training data.

GRaPE 2 will come sooner than the GRaPE 1 family had, and will show multiple improvements.

There are no benchmarks for GRaPE 1 Models due to the costly nature of running them, as well as prioritization of newer models.

Updates for GRaPE 2 models will be posted here on Huggingface, as well as [Skinnertopia](https://www.skinnertopia.com/)