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1.4 KiB
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.