Instructions to use Jonnester/Purrence-3M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
File size: 632 Bytes
921bf58 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"vocab_size": 2048,
"width": 384,
"heads": 6,
"mlp_width": 2096,
"loops": 6,
"rank": 128,
"controller_width": 16,
"max_seq_len": 8192,
"norm_eps": 1e-06,
"routing_eps": 1.1920928955078125e-07,
"model_type": "purrence",
"architectures": [
"PurrenceForCausalLM"
],
"torch_dtype": "float32",
"bos_token_id": 2047,
"eos_token_id": 2047,
"pad_token_id": 2047,
"tie_word_embeddings": true,
"use_cache": false,
"max_position_embeddings": 8192,
"auto_map": {
"AutoConfig": "configuration_purrence.PurrenceConfig",
"AutoModelForCausalLM": "modeling_purrence.PurrenceForCausalLM"
}
}
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