arcflare_
Code14B official

qwen2.5-coder-14b-instruct

by Qwen

Instruction-tuned 14B code model with improved code generation, reasoning and fixing, and long-context support up to 128K tokens.

#code#instruct
arcflare pull Qwen/Qwen2.5-Coder-14B-Instruct-GGUF:q4_k_m

[ 01 ] // quickstart

┌─ arcflare — zsh // tty1
$ 

[ 02 ] // readme

qwen2.5-coder-14b-instruct

Instruction-tuned 14B code model with improved code generation, reasoning and fixing, and long-context support up to 128K tokens.

Get it

arcflare pull Qwen/Qwen2.5-Coder-14B-Instruct-GGUF:q4_k_m
arcflare run qwen2.5-coder-14b-instruct

ArcFlare reads the GGUF header and loads it at the largest context your free VRAM can actually hold. Use arcflare fit to see that before downloading anything else, or arcflare use opencode to code with it.

Highlights

  • Downloads the q4_k_m file by default: 9 GB. Also published: q5_k_m (10.5 GB), q6_k (12.1 GB), q8_0 (15.7 GB)
  • Trained for a 128K context
  • Licence: Apache-2.0. Read it before commercial use

Sizes

  • 14b · 9GB

Other sizes live in sibling repos: swap the size in the repo name when pulling.

[ 03 ] // relatedmore →

qwen2.5-coder

Alibaba Qwen

Code

Code-specific instruction-tuned 7B Qwen2.5-Coder model, improved at code generation, code reasoning and code fixing.

size
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vram
~6 GB
license
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25% of a 24 GB card

#code #instruct

qwen2.5-coder-32b

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Code-specific instruction-tuned 32B Qwen2.5-Coder model, improved at code generation, code reasoning and code fixing.

size
32B
vram
~21 GB
license
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88% of a 24 GB card

#code #instruct #large

starcoder2

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Code

Code LLM self-aligned from StarCoder2-15B with a fully permissive, transparent pipeline and no human annotations or distilled data.

size
15B
vram
~11 GB
license
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46% of a 24 GB card

#code #instruct