Downloads · 30 days
26
16% of all-time downloads
radm/prophet-qwen3-4b-sft-Q8_0-GGUF
prophet-qwen3-4b-sft-Q8_0-GGUF is a machine learning model from radm. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
<img src="https://huggingface.co/radm/prophet-qwen3-4b-sft/resolve/main/model-image.png" alt="Model Image" width="100%"
Downloads · 30 days
26
16% of all-time downloads
All-time downloads
160
Public
Repo size
4.3 GB
Likes
0
Public
Click a slice to open those files.
.gguf4.3 GB · 100%
From the Hugging Face model README
This model was converted to GGUF format from radm/prophet-qwen3-4b-sft using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
For chat templapte errors (eg lmstudio) use this issue.
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
llama-cli --hf-repo radm/prophet-qwen3-4b-sft-Q8_0-GGUF --hf-file prophet-qwen3-4b-sft-q8_0.gguf -p "The meaning to life and the universe is"
llama-server --hf-repo radm/prophet-qwen3-4b-sft-Q8_0-GGUF --hf-file prophet-qwen3-4b-sft-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 radm/prophet-qwen3-4b-sft-Q8_0-GGUF --hf-file prophet-qwen3-4b-sft-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo radm/prophet-qwen3-4b-sft-Q8_0-GGUF --hf-file prophet-qwen3-4b-sft-q8_0.gguf -c 2048