GraySoft
Projects Models Compare Cloud benchmarks FAQ Download guIDE →
Model Intelligence Sheet

Chopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF overview

Chopinab/LLaDA 8B Instruct Q4 K M GGUF This model was converted to GGUF format from GSAI ML/LLaDA 8B Instruct https://huggingface.co/GSAI ML/LLaDA 8B Instruct …

transformersggufllama-cppgguf-my-repotext-generationbase_model:GSAI-ML/LLaDA-8B-Instructbase_model:quantized:GSAI-ML/LLaDA-8B-Instructlicense:mitendpoints_compatibleregion:usconversational

Runs locally from ~4.59 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
0
Likes
0
Pipeline
text-generation
Author

Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
llada-8b-instruct-q4_k_m.ggufGGUFQ4_K_M4.59 GBDownload

Model Details

Model IDChopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF
AuthorChopinab
Pipelinetext-generation
Licensemit
Base modelGSAI-ML/LLaDA-8B-Instruct
Last modified2026-10-17T14:32:17.000Z

Model README

---

license: mit

library_name: transformers

pipeline_tag: text-generation

tags:

  • llama-cpp
  • gguf-my-repo

base_model: GSAI-ML/LLaDA-8B-Instruct

---

Chopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF

This model was converted to GGUF format from GSAI-ML/LLaDA-8B-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space.

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 Chopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF --hf-file llada-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Chopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF --hf-file llada-8b-instruct-q4_k_m.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 Chopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF --hf-file llada-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Chopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF --hf-file llada-8b-instruct-q4_k_m.gguf -c 2048

Run Chopinab/LLaDA-8B-Instruct-Q4_K_M-GGUF with guIDE

Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.

Download guIDE → · Browse 524k+ models · Compare models

Source: Hugging Face · Compare models