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Dev-in-the-BM/business-news-generator-Q8_0-GGUF overview

Dev in the BM/business news generator Q8 0 GGUF This model was converted to GGUF format from Emil7018/business news generator https://huggingface.co/Emil7018/b…

transformersggufgenerated_from_trainerllama-cppgguf-my-repobase_model:Emil7018/business-news-generatorbase_model:quantized:Emil7018/business-news-generatorlicense:apache-2.0endpoints_compatibleregion:us

Runs locally from ~138.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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business-news-generator-q8_0.ggufGGUFQ8_0138.1 MBDownload

Model Details

Model IDDev-in-the-BM/business-news-generator-Q8_0-GGUF
AuthorDev-in-the-BM
Pipeline—
Licenseapache-2.0
Base modelEmil7018/business-news-generator
Last modified2026-10-14T09:13:13.000Z

Model README

---

library_name: transformers

license: apache-2.0

base_model: Emil7018/business-news-generator

tags:

  • generated_from_trainer
  • llama-cpp
  • gguf-my-repo

model-index:

  • name: business-news-generator

results: []

---

Dev-in-the-BM/business-news-generator-Q8_0-GGUF

This model was converted to GGUF format from Emil7018/business-news-generator 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 Dev-in-the-BM/business-news-generator-Q8_0-GGUF --hf-file business-news-generator-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Dev-in-the-BM/business-news-generator-Q8_0-GGUF --hf-file business-news-generator-q8_0.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 Dev-in-the-BM/business-news-generator-Q8_0-GGUF --hf-file business-news-generator-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Dev-in-the-BM/business-news-generator-Q8_0-GGUF --hf-file business-news-generator-q8_0.gguf -c 2048

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