Instructions to use typer-org/booper-story-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use typer-org/booper-story-v1 with Transformers:

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

pipe = pipeline("text-generation", model="typer-org/booper-story-v1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("typer-org/booper-story-v1")
model = AutoModelForCausalLM.from_pretrained("typer-org/booper-story-v1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use typer-org/booper-story-v1 with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/typer-org/booper-story-v1

SGLang

How to use typer-org/booper-story-v1 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 "typer-org/booper-story-v1" \
    --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": "typer-org/booper-story-v1",
		"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 "typer-org/booper-story-v1" \
        --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": "typer-org/booper-story-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use typer-org/booper-story-v1 with Docker Model Runner:
```
docker model run hf.co/typer-org/booper-story-v1
```

booper-story-v1

Long-form SFT of ProCreations/Booper-Big-Chat-INT8 (Mixtral MoE, 150M total / ~50M active, vocab 16384) so booper answers story/long-answer requests instead of one-liners. Trained with sft/sft_longform.py from https://github.com/frgmt0/babble in the pair layout <bos> prompt <sep> response <eos> (loss on the response).

Data mix

tinystories: 54000 examples
no_robots: 8387 examples
discord: 48000 examples

Training

steps: 910, tokens: 27,998,826
val loss: 2.4375 -> 1.3351
device: mps, lr 4e-05, seq len 1024

Samples (temperature 0.8)

write me a short story about a dragon who is afraid of fire

Once upon a time there was a dragon called Tim. He wanted to be afraid of fire when he saw the dragon fluttering around. The dragon thought for a moment and then ran up to his friend. She said, "I'm afraid, but you have to go home first. Let's move on from the fearful dragon

tell me a story

I got upset at the beginning of the morning for a while and it started to rain outside.

Soon it was time for the rain. The rain stopped and it was all gone. I was so sad

hey booper whats up

My guy and me both don’t know who I am

Loading

Same INT8 layout as the base: load_int8.py in this repo, or babble.hfserve with BABBLE_HF_MODEL_DIR pointed at a snapshot.

Downloads last month: 210

Model tree for typer-org/booper-story-v1

Base model

ProCreations/Booper-Big

Finetuned

ProCreations/Booper-Big-Chat

Finetuned

ProCreations/Booper-Big-Chat-INT8

Finetuned

(2)

this model