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bamgjr/Qwen2.5-Coder-7B-Instruct-IQ4_NL-GGUF overview

bamgjr/Qwen2.5 Coder 7B Instruct IQ4 NL GGUF This model was converted to GGUF format from Qwen/Qwen2.5 Coder 7B Instruct https://huggingface.co/Qwen/Qwen2.5 Co…

transformersggufcodecodeqwenchatqwenqwen-coderllama-cppgguf-my-repotext-generationenbase_model:Qwen/Qwen2.5-Coder-7B-Instructbase_model:quantized:Qwen/Qwen2.5-Coder-7B-Instructlicense:apache-2.0endpoints_compatibleregion:usimatrixconversational

Runs locally from ~4.13 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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text-generation
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Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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qwen2.5-coder-7b-instruct-iq4_nl-imat.ggufGGUFIQ4_NL4.13 GBDownload

Model Details

Model IDbamgjr/Qwen2.5-Coder-7B-Instruct-IQ4_NL-GGUF
Authorbamgjr
Pipelinetext-generation
Licenseapache-2.0
Base modelQwen/Qwen2.5-Coder-7B-Instruct
Last modified2026-07-13T06:27:15.000Z

Model README

---

license: apache-2.0

license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct/blob/main/LICENSE

language:

  • en

base_model: Qwen/Qwen2.5-Coder-7B-Instruct

pipeline_tag: text-generation

library_name: transformers

tags:

  • code
  • codeqwen
  • chat
  • qwen
  • qwen-coder
  • llama-cpp
  • gguf-my-repo

---

bamgjr/Qwen2.5-Coder-7B-Instruct-IQ4_NL-GGUF

This model was converted to GGUF format from Qwen/Qwen2.5-Coder-7B-Instruct using llama.cpp.

Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo bamgjr/Qwen2.5-Coder-7B-Instruct-IQ4_NL-GGUF --hf-file qwen2.5-coder-7b-instruct-iq4_nl-imat.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo bamgjr/Qwen2.5-Coder-7B-Instruct-IQ4_NL-GGUF --hf-file qwen2.5-coder-7b-instruct-iq4_nl-imat.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo bamgjr/Qwen2.5-Coder-7B-Instruct-IQ4_NL-GGUF --hf-file qwen2.5-coder-7b-instruct-iq4_nl-imat.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo bamgjr/Qwen2.5-Coder-7B-Instruct-IQ4_NL-GGUF --hf-file qwen2.5-coder-7b-instruct-iq4_nl-imat.gguf -c 2048

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