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CurtHaw/STEM-Oracle-27B-Q3_K_M-GGUF overview

CurtHaw/STEM Oracle 27B Q3 K M GGUF This model was converted to GGUF format from Verdugie/STEM Oracle 27B https://huggingface.co/Verdugie/STEM Oracle 27B using…

transformersggufconversationalstemtutormathphysicschemistrybiologycomputer-scienceclaude-distillationopusdensity-optimized27b-densellama-cppgguf-my-repotext-generationenesbase_model:Verdugie/STEM-Oracle-27Bbase_model:quantized:Verdugie/STEM-Oracle-27Blicense:apache-2.0endpoints_compatibleregion:us

Runs locally from ~10.4 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation
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Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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stem-oracle-27b-q3_k_m.ggufGGUFQ3_K_M10.4 MBDownload

Model Details

Model IDCurtHaw/STEM-Oracle-27B-Q3_K_M-GGUF
AuthorCurtHaw
Pipelinetext-generation
Licenseapache-2.0
Base modelVerdugie/STEM-Oracle-27B
Last modified2026-07-02T06:57:19.000Z

Model README

---

license: apache-2.0

language:

  • en
  • es

base_model: Verdugie/STEM-Oracle-27B

tags:

  • conversational
  • stem
  • tutor
  • math
  • physics
  • chemistry
  • biology
  • computer-science
  • gguf
  • claude-distillation
  • opus
  • density-optimized
  • 27b-dense
  • llama-cpp
  • gguf-my-repo

library_name: transformers

pipeline_tag: text-generation

---

CurtHaw/STEM-Oracle-27B-Q3_K_M-GGUF

This model was converted to GGUF format from Verdugie/STEM-Oracle-27B 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 CurtHaw/STEM-Oracle-27B-Q3_K_M-GGUF --hf-file stem-oracle-27b-q3_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo CurtHaw/STEM-Oracle-27B-Q3_K_M-GGUF --hf-file stem-oracle-27b-q3_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 CurtHaw/STEM-Oracle-27B-Q3_K_M-GGUF --hf-file stem-oracle-27b-q3_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo CurtHaw/STEM-Oracle-27B-Q3_K_M-GGUF --hf-file stem-oracle-27b-q3_k_m.gguf -c 2048

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