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rpatel622/tmax-4b-Q4_K_M-GGUF overview

rpatel622/tmax 4b Q4 K M GGUF This model was converted to GGUF format from allenai/tmax 4b https://huggingface.co/allenai/tmax 4b using llama.cpp via the ggml.…

ggufllama-cppgguf-my-repodataset:allenai/tmax-15k-open-instructbase_model:allenai/tmax-4bbase_model:quantized:allenai/tmax-4blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~2.52 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Model Details

Model IDrpatel622/tmax-4b-Q4_K_M-GGUF
Authorrpatel622
Pipeline
Licenseapache-2.0
Base modelallenai/tmax-4b
Last modified2026-06-27T16:51:14.000Z

Model README

---

license: apache-2.0

datasets:

  • allenai/tmax-15k-open-instruct

base_model: allenai/tmax-4b

tags:

  • llama-cpp
  • gguf-my-repo

---

rpatel622/tmax-4b-Q4_K_M-GGUF

This model was converted to GGUF format from allenai/tmax-4b 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 rpatel622/tmax-4b-Q4_K_M-GGUF --hf-file tmax-4b-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo rpatel622/tmax-4b-Q4_K_M-GGUF --hf-file tmax-4b-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 rpatel622/tmax-4b-Q4_K_M-GGUF --hf-file tmax-4b-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo rpatel622/tmax-4b-Q4_K_M-GGUF --hf-file tmax-4b-q4_k_m.gguf -c 2048

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