Pacific-Prime/python-node

Pacific-Prime: Python Node

Pure Python specialist fine-tuned from Pacific-Prime Code (I64 architecture, 1.5B parameters).

Skills

• Python basics & standard library
• Algorithms & data structures
• Object-oriented programming
• Decorators & generators
• List comprehensions
• File I/O & error handling

Training

• Architecture: I64 (Complexity-Deep)
• Parameters: 1.5B
• Base model: pacific-prime-code (checkpoint epoch 70)
• Method: Full SFT (no LoRA)
• Dataset: python_code_instructions_18k_alpaca (18K samples)
• Epochs: 1000
• Max context: 4096 tokens

Inference with vLLM-I64

Use our custom vLLM engine with native I64 support:

👉 vllm-i64

git clone https://github.com/Complexity-ML/vllm-i64.git
cd vllm-i64
pip install -e .

from vllm import LLM, SamplingParams

model = LLM(model="Pacific-Prime/python-node")
params = SamplingParams(temperature=0.7, max_tokens=4096)

prompt = "User: Write a Python function to find the longest common subsequence of two strings.\nAssistant:"
output = model.generate([prompt], params)
print(output[0].outputs[0].text)

Serve Your Own I64 Model

Trained your own I64 model with complexity-deep? Serve it with vllm-i64:

from vllm import LLM, SamplingParams

model = LLM(model="/path/to/your/i64-model")
params = SamplingParams(temperature=0.7, max_tokens=4096)
output = model.generate(["User: Hello!\nAssistant:"], params)
print(output[0].outputs[0].text)

Links

• Complexity Framework — ML framework for building & training I64 models
• Complexity-Deep — Training framework & architecture
• vllm-i64 — Inference engine for I64 models

License

CC BY-NC 4.0