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Gridexis/SmolLM2-135M-Instruct-Q8_0-GGUF overview

Gridexis/SmolLM2 135M Instruct Q8 0 GGUF This model was converted to GGUF format from HuggingFaceTB/SmolLM2 135M Instruct https://huggingface.co/HuggingFaceTB/…

transformersggufsafetensorsonnxtransformers.jsllama-cppgguf-my-repotext-generationenbase_model:HuggingFaceTB/SmolLM2-135M-Instructbase_model:quantized:HuggingFaceTB/SmolLM2-135M-Instructlicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~138.1 MB disk (4 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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smollm2-135m-instruct-q8_0.ggufGGUFQ8_0138.1 MBDownload

Model Details

Model IDGridexis/SmolLM2-135M-Instruct-Q8_0-GGUF
AuthorGridexis
Pipelinetext-generation
Licenseapache-2.0
Base modelHuggingFaceTB/SmolLM2-135M-Instruct
Last modified2026-08-09T18:52:43.000Z

Model README

---

library_name: transformers

license: apache-2.0

language:

  • en

pipeline_tag: text-generation

tags:

  • safetensors
  • onnx
  • transformers.js
  • llama-cpp
  • gguf-my-repo

base_model: HuggingFaceTB/SmolLM2-135M-Instruct

---

Gridexis/SmolLM2-135M-Instruct-Q8_0-GGUF

This model was converted to GGUF format from HuggingFaceTB/SmolLM2-135M-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 Gridexis/SmolLM2-135M-Instruct-Q8_0-GGUF --hf-file smollm2-135m-instruct-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Gridexis/SmolLM2-135M-Instruct-Q8_0-GGUF --hf-file smollm2-135m-instruct-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 Gridexis/SmolLM2-135M-Instruct-Q8_0-GGUF --hf-file smollm2-135m-instruct-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Gridexis/SmolLM2-135M-Instruct-Q8_0-GGUF --hf-file smollm2-135m-instruct-q8_0.gguf -c 2048

Run Gridexis/SmolLM2-135M-Instruct-Q8_0-GGUF with guIDE

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