Instructions to use x5tne/playdate-70-140 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use x5tne/playdate-70-140 with Transformers:

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

pipe = pipeline("text-generation", model="x5tne/playdate-70-140")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("x5tne/playdate-70-140")
model = AutoModelForCausalLM.from_pretrained("x5tne/playdate-70-140")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use x5tne/playdate-70-140 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "x5tne/playdate-70-140"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "x5tne/playdate-70-140",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/x5tne/playdate-70-140

SGLang

How to use x5tne/playdate-70-140 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 "x5tne/playdate-70-140" \
    --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": "x5tne/playdate-70-140",
		"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 "x5tne/playdate-70-140" \
        --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": "x5tne/playdate-70-140",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use x5tne/playdate-70-140 with Docker Model Runner:
```
docker model run hf.co/x5tne/playdate-70-140
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Not recommended for use.

Due to the amount of attention this proof of concept model has recieved, I advice against usage and for people to focus on my newer models. Models listed below.

Playdate SmolLM2-135M: 10k Samples

Playdate SmolLM2-135M: 5k samples

Playdate DistilGPT2: 5k samples (Unreliable)