SixOpen/granite-34b-code-instruct-Q5_K_M-GGUF
This model was converted to GGUF format from ibm-granite/granite-34b-code-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.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo SixOpen/granite-34b-code-instruct-Q5_K_M-GGUF --model granite-34b-code-instruct.Q5_K_M.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo SixOpen/granite-34b-code-instruct-Q5_K_M-GGUF --model granite-34b-code-instruct.Q5_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.
git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m granite-34b-code-instruct.Q5_K_M.gguf -n 128
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Model tree for SixOpen/granite-34b-code-instruct-Q5_K_M-GGUF
Base model
ibm-granite/granite-34b-code-base-8kDatasets used to train SixOpen/granite-34b-code-instruct-Q5_K_M-GGUF
Evaluation results
- pass@1 on HumanEvalSynthesis(Python)self-reported62.200
- pass@1 on HumanEvalSynthesis(Python)self-reported56.700
- pass@1 on HumanEvalSynthesis(Python)self-reported62.800
- pass@1 on HumanEvalSynthesis(Python)self-reported47.600
- pass@1 on HumanEvalSynthesis(Python)self-reported57.900
- pass@1 on HumanEvalSynthesis(Python)self-reported41.500
- pass@1 on HumanEvalSynthesis(Python)self-reported53.000
- pass@1 on HumanEvalSynthesis(Python)self-reported45.100
- pass@1 on HumanEvalSynthesis(Python)self-reported50.600
- pass@1 on HumanEvalSynthesis(Python)self-reported36.000