Files

1.4 KiB

zen-coder

Model Details

  • Model Type: code-generation
  • Version: 1.2.0
  • Author: Hanzo AI
  • License: Apache-2.0
  • Base Model: Original architecture

Architecture

  • Context Length: 16,384 tokens
  • Vocabulary Size: 40,000
  • Hidden Size: 2048
  • Number of Layers: 28
  • Number of Heads: 16

Capabilities

  • code-generation
  • code-completion
  • code-explanation
  • debugging

Special Tokens

{
  "<s>": "bos_token",
  "</s>": "eos_token",
  "<pad>": "pad_token",
  "<|code|>": "code_start",
  "<|/code|>": "code_end",
  "<|language:": "language_tag",
  "<|explain|>": "explanation_start",
  "<|/explain|>": "explanation_end"
}

Training

  • Training Data: Hanzo code dataset (150+ languages)
  • Has Thinking: No

Usage

This model has been converted to GGUF format for use with llama.cpp.

Example Usage

# Run with llama.cpp
./llama-cli -m zen-coder-Q5_K_M.gguf \
    --ctx-size 16384 \
    --temp 0.7 \
    --top-p 0.9 \
    --prompt "Your prompt here"

Quantization Variants

Multiple quantization levels are available:

  • Q4_K_M: Balanced quality and size (~4 bits per weight)
  • Q5_K_M: Higher quality (~5 bits per weight)
  • Q6_K: Even higher quality (~6 bits per weight)
  • Q8_0: Near-lossless quality (~8 bits per weight)
  • FP16: Full precision (16 bits per weight)

Choose based on your hardware capabilities and quality requirements.