Merkium/ puma-1.0:latest

6 21 hours ago

1.42B open-weight Llama-architecture language and coding model with a custom 49k BPE tokenizer and 32K context window for fast CPU and mobile inference. 

ollama run Merkium/puma-1.0

Details

21 hours ago

a092438f7ed1 · 1.5GB

model
llama
·
1.42B
·
Q8_0
template
<|bos|>{{- if .Messages }}{{- if .System }}<|system|> {{ .System }}<|eos|> {{ end }}{{- range .Messa
system
You are Puma 1.0, an open-weight 1.42B-parameter AI assistant and coding model created by Merkium an
license
Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR US
params
{ "num_ctx": 8192, "repeat_penalty": 1.08, "stop": [ "<|eos|>", "<|user|

Readme

Puma 1.0

Puma 1.0 is a 1.42-billion-parameter (1,418,911,232 parameters) open-weight language and code generation model created by Merkium and released under the Apache 2.0 license. Built on a 28-layer LlamaForCausalLM decoder (hidden_size = 1536, intermediate_size = 9216, 6:1 Grouped-Query Attention, 32K RoPE) paired with a custom 49,152-token byte-level BPE vocabulary, it runs locally on desktop CPUs, laptops, and smartphones in ~1.44 GB (Q8_0 GGUF).

Quickstart

ollama run Merkium/puma-1.0

Architecture

Specification Value
Architecture 28-layer pre-norm Transformer decoder (LlamaForCausalLM, arch: llama)
Parameters 1,418,911,232 (1.42B, tied embeddings)
Dimensions hidden_size = 1536, intermediate_size = 9216 (6.0x SwiGLU), 12 Q / 2 KV heads
Context Window 32,768 tokens (num_ctx = 8192 default)
Vocabulary 49,152 custom byte-level BPE (`<
Quantization Q8_0 (1.44 GB)
License Apache-2.0

Capabilities

  • Software Engineering & Scripting: Generates clean Python, SQL, Bash, regexes, data structures, and unit tests (90% Python AST validity, 70% strict unit-test pass rate on held-out algorithmic tasks).
  • Multi-Turn Local Assistant: Handles casual conversation, technical Q&A, text summarization, and structured JSON / Markdown output across multi-turn sessions.
  • CPU & Mobile Deployment: Runs at 55-95 tok/s on Apple Silicon, 20-40 tok/s on x86_64 AVX2 CPUs, and 12-28 tok/s offline on iOS/Android (PocketPal AI, Termux) via Ueuee82683/Puma-1.0.

Local API Usage (Python)

from openai import OpenAI

client = OpenAI(base_url="http://localhost:11434/v1", api_key="ollama")
resp = client.chat.completions.create(
    model="Merkium/puma-1.0",
    messages=[{"role": "user", "content": "Write a Python function is_prime(n) with type hints."}],
    temperature=0.3,
)
print(resp.choices[0].message.content)

Links