uCoder-8b-base-GGUF

uCoder-8b-base-GGUF

Quantized GGUF models converted from uaytug/uCoder-8b-base.

Converted using the latest llama.cpp (CUDA-accelerated quantization).

Available Files

16-bit

• uCoder-8b-base-BF16.gguf → Highest precision float (similar to original, ~16 GB)

8-bit

• uCoder-8b-base-Q8_0.gguf → Near-lossless

6-bit

• uCoder-8b-base-Q6_K.gguf

5-bit

• uCoder-8b-base-Q5_K_S.gguf
• uCoder-8b-base-Q5_K_M.gguf → Great quality

4-bit (most popular range)

• uCoder-8b-base-Q4_K_M.gguf → Recommended balance
• uCoder-8b-base-Q4_K_S.gguf
• uCoder-8b-base-Q4_1.gguf

3-bit

• uCoder-8b-base-Q3_K_S.gguf
• uCoder-8b-base-Q3_K_M.gguf

2-bit

• uCoder-8b-base-Q2_K.gguf

Original Model Information

uCoder-8b-base

uCoder-8b-base is a coding-specialized 8B parameter model created by TIES-merging five high-quality distilled models based on Qwen3-8B. This merge is designed to combine advanced reasoning capabilities with state-of-the-art coding performance, making it an ideal base for further instruction tuning or direct code generation tasks.

🚀 Model Description

This model leverages the TIES (Trimming, Electing, and Signs) merging method to effectively combine the weights of multiple expert models without losing the specific competencies of each. By normalizing the weights and focusing on high-reasoning distillations from top-tier frontier models (GPT-5.x, Claude 4.5, etc.), uCoder-8b-base achieves a robust balance between logic and syntax accuracy.

Key Features

• High Reasoning: Inherits logic handling from Claude and GPT-based distills.
• Polyglot Coding: Proficient in Python, JavaScript, C++, Rust, and other major languages.
• Base Model: Built on the powerful Qwen3-8B architecture.
• Efficient: 8B size allows for local inference on consumer hardware (12GB+ VRAM recommended for FP16, less for quantized).

🧩 Merged Models

The following models were merged using equal weights to create uCoder-8b-base:

Limitations

• Base Model Nature: This is a base model (merge), not fully instruction-tuned for chat. While it can handle chat formats, it performs best when fine-tuned or given specific few-shot examples.
• Coding Focus: While capable of general reasoning, its domain expertise is heavily skewed towards programming and technical tasks.

License

This model is released under the Apache 2.0 license.