Instructions to use LocalWisdom/Penny-Alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LocalWisdom/Penny-Alpha with Transformers:

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

pipe = pipeline("text-generation", model="LocalWisdom/Penny-Alpha", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("LocalWisdom/Penny-Alpha", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LocalWisdom/Penny-Alpha with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/LocalWisdom/Penny-Alpha

SGLang

How to use LocalWisdom/Penny-Alpha 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 "LocalWisdom/Penny-Alpha" \
    --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": "LocalWisdom/Penny-Alpha",
		"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 "LocalWisdom/Penny-Alpha" \
        --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": "LocalWisdom/Penny-Alpha",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LocalWisdom/Penny-Alpha with Docker Model Runner:
```
docker model run hf.co/LocalWisdom/Penny-Alpha
```

Fix typo in architecture name

by BananaMindBot - opened 3 days ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-2

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -10,9 +10,9 @@ tags:
 ---
 # Penny Alpha
-A 59M parameters model with Deepseek V4.1 Flash architechture
 Other formats:
  - GGUF: https://huggingface.co/LocalWisdom/Penny-Alpha-GGUF
-Trained on 1B tokens of Ultra-FineWeb-L3 over 1 day 12 hours using 1x RTX 5060 Ti costing us $5.64.

 ---
 # Penny Alpha
+A 59M parameters model with Deepseek V4.1 Flash architecture
 Other formats:
  - GGUF: https://huggingface.co/LocalWisdom/Penny-Alpha-GGUF
+Trained on 1B tokens of Ultra-FineWeb-L3 over 1 day 12 hours using 1x RTX 5060 Ti costing us $5.64.