Instructions to use Jonnester/Purrence-3M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Jonnester/Purrence-3M with Transformers:

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

pipe = pipeline("text-generation", model="Jonnester/Purrence-3M", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Jonnester/Purrence-3M", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Jonnester/Purrence-3M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Jonnester/Purrence-3M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Jonnester/Purrence-3M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Jonnester/Purrence-3M

SGLang

How to use Jonnester/Purrence-3M 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 "Jonnester/Purrence-3M" \
    --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": "Jonnester/Purrence-3M",
		"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 "Jonnester/Purrence-3M" \
        --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": "Jonnester/Purrence-3M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Jonnester/Purrence-3M with Docker Model Runner:
```
docker model run hf.co/Jonnester/Purrence-3M
```

Purrence-3M

File size: 284 Bytes

921bf58

{
  "tokenizer_sha256": "fc240b741112488b639a711f502305601e3b8a1b01c5ae93a48b9ae55692dd33",
  "tokenizers_version": "0.20.3",
  "vocab_size": 2048,
  "boundary_special": {
    "id": 2047,
    "purpose": "structurally injected document boundary",
    "spelling": "<|endoftext|>"
  }
}