Instructions to use erdiari/Mistral-Scary-Story-Finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use erdiari/Mistral-Scary-Story-Finetune with Transformers:

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

pipe = pipeline("text-generation", model="erdiari/Mistral-Scary-Story-Finetune")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("erdiari/Mistral-Scary-Story-Finetune")
model = AutoModelForCausalLM.from_pretrained("erdiari/Mistral-Scary-Story-Finetune", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use erdiari/Mistral-Scary-Story-Finetune 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 erdiari/Mistral-Scary-Story-Finetune:F16
# Run inference directly in the terminal:
llama cli -hf erdiari/Mistral-Scary-Story-Finetune:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf erdiari/Mistral-Scary-Story-Finetune:F16
# Run inference directly in the terminal:
llama cli -hf erdiari/Mistral-Scary-Story-Finetune:F16

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf erdiari/Mistral-Scary-Story-Finetune:F16
# Run inference directly in the terminal:
./build/bin/llama cli -hf erdiari/Mistral-Scary-Story-Finetune:F16

Use Docker

docker model run hf.co/erdiari/Mistral-Scary-Story-Finetune:F16

Llama new
LM Studio
Jan

vLLM

How to use erdiari/Mistral-Scary-Story-Finetune with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/erdiari/Mistral-Scary-Story-Finetune:F16

SGLang

How to use erdiari/Mistral-Scary-Story-Finetune 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 "erdiari/Mistral-Scary-Story-Finetune" \
    --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": "erdiari/Mistral-Scary-Story-Finetune",
		"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 "erdiari/Mistral-Scary-Story-Finetune" \
        --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": "erdiari/Mistral-Scary-Story-Finetune",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use erdiari/Mistral-Scary-Story-Finetune with Ollama:
```
ollama run hf.co/erdiari/Mistral-Scary-Story-Finetune:F16
```
Unsloth Desktop
Docker Model Runner
How to use erdiari/Mistral-Scary-Story-Finetune with Docker Model Runner:
```
docker model run hf.co/erdiari/Mistral-Scary-Story-Finetune:F16
```

Lemonade

How to use erdiari/Mistral-Scary-Story-Finetune with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull erdiari/Mistral-Scary-Story-Finetune:F16

Run and chat with the model

lemonade run user.Mistral-Scary-Story-Finetune-F16

List all available models

lemonade list

Atomic Chat
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Mistral Scary Story Finetune

This model is a finetune of mistralai/Mistral-7B-v0.1 using r/nosleep subreddit as data. This is not an instruction fine tuned model and only fine tuned on stories. To generate a story, give a title to model like:

# On a dark and spooky night

You can even write some of the story get a better result.

Training Procedure

This is a lora fine-tune with following parameters:

r=8,
lora_alpha=16,
lora_dropout=0.05

Downloads last month: 33

Safetensors

Model size

7B params

Tensor type

BF16

Model tree for erdiari/Mistral-Scary-Story-Finetune

Quantizations

2 models