Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:# Run inference directly in the terminal:
llama-cli -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:# Run inference directly in the terminal:
./llama-cli -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:Use Docker
docker model run hf.co/LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:Everyone-Coder-33b-v2-Base
EveryoneLLM series of models made by the community, for the community. This is a coding specific model made using fine-tunes of deekseekcoder-33b-base.
This Version 2 of the Everything-Coder-33b model uses the task_arithmetic merging method which has major increases in coding performance as opposed to the ties method. You should find this version having much better coding performance than Version 1, without any of the negative that merging has on the integrity of the model.
Prompt template: Alpaca
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
The models that were used in this merger were as follow:
Thank you to the creators of the above ai models, they have full credit for the EveryoneLLM series of models. Without their hard work we wouldnt be able to achieve the great success we have in the open source community. 💗
You can find the write up for merging models here:
https://docs.google.com/document/d/1_vOftBnrk9NRk5h10UqrfJ5CDih9KBKL61yvrZtVWPE/edit?usp=sharing
Config for the merger can be found bellow:
models:
- model: codefuse-ai_CodeFuse-DeepSeek-33B
parameters:
weight: 1
- model: deepseek-ai_deepseek-coder-33b-instruct
parameters:
weight: 1
- model: WizardLM_WizardCoder-33B-V1.1
parameters:
weight: 1
merge_method: task_arithmetic
base_model: deepseek-ai_deepseek-coder-33b-base
parameters:
normalize: true
int8_mask: true
dtype: float16
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Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF:# Run inference directly in the terminal: llama-cli -hf LoneStriker/Everyone-Coder-33b-v2-Base-GGUF: