Skywork R1V3 38B Q8 0 GGUF
This model was converted to GGUF format from Skywork/Skywork-R1V3-38B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 32,4 GB
- Modelo base
- Skywork/Skywork-R1V3-38B
- Versión
- vRevision 30ea88d
- Actualizado
- 24 oct 2026
- Descargas
- 7
- Fuente
- Hugging Face
Descripción de la fuente
ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF
This model was converted to GGUF format from Skywork/Skywork-R1V3-38B 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 ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-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 ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-q8_0.gguf -c 2048
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 24 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- pipeline_tag: visual-question-answering library_name: transformers license: mit language: - en base_model: Skywork/Skywork-R1V3-38B tags: - Skywork R1V - llama-cpp - gguf-my-repo --- # ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF This model was converted to GGUF format from [`Skywork/Skywork-R1V3-38B`](https://huggingface.co/Skywork/Skywork-R1V3-38B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/Skywork/Skywork-R1V3-38B) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-q8_0.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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 ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF --hf-file skywork-r1v3-38b-q8_0.gguf -c 2048 ```
Source context: 7 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF
Source context: 27 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo ClintHardwood/Skywork-R1V3-38B-Q8_0-GGUF
