Downloads · 30 days
17
10% of all-time downloads
sh2nd/codegemma-1.1-2b-fix-Q4_K_M-GGUF
codegemma-1.1-2b-fix-Q4_K_M-GGUF is a machine learning model from sh2nd. 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. The card lists the license as gemma.
This is a fix for CodeGemma 1.1 2B not working properly with Ollama and Continue as of August 2024.
Downloads · 30 days
17
10% of all-time downloads
All-time downloads
164
Public
Repo size
1.6 GB
Likes
0
Public
Click a slice to open those files.
.gguf1.6 GB · 100%
From the Hugging Face model README
This is a fix for CodeGemma 1.1 2B not working properly with Ollama and Continue as of August 2024.
Create the following model file and save it as modelfile.
FROM codegemma-1.1-2b-fix-q4_k_m.gguf
TEMPLATE "{{- if .Suffix }}<|fim_prefix|>{{ .Prompt }}<|fim_suffix|>{{ .Suffix }}<|fim_middle|>
{{- else }}{{ .Prompt }}
{{- end }}"
PARAMETER repeat_penalty 1
PARAMETER stop <|fim_prefix|>
PARAMETER stop <|fim_suffix|>
PARAMETER stop <|fim_middle|>
PARAMETER stop <|file_separator|>
Create an Ollama model with the following command.
ollama create codegemma:2b-code-v1.1-q4_K_M-fix --file modelfile
This model was converted to GGUF format from sh2nd/codegemma-1.1-2b-fix using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
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 sh2nd/codegemma-1.1-2b-fix-Q4_K_M-GGUF --hf-file codegemma-1.1-2b-fix-q4_k_m.gguf -p "The meaning to life and the universe is"
llama-server --hf-repo sh2nd/codegemma-1.1-2b-fix-Q4_K_M-GGUF --hf-file codegemma-1.1-2b-fix-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 sh2nd/codegemma-1.1-2b-fix-Q4_K_M-GGUF --hf-file codegemma-1.1-2b-fix-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo sh2nd/codegemma-1.1-2b-fix-Q4_K_M-GGUF --hf-file codegemma-1.1-2b-fix-q4_k_m.gguf -c 2048