How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf rovdetection/code-1b-chat-v2-gguf:Q4_K_M# Run inference directly in the terminal:
llama cli -hf rovdetection/code-1b-chat-v2-gguf:Q4_K_MUse 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 rovdetection/code-1b-chat-v2-gguf:Q4_K_M# Run inference directly in the terminal:
./llama-cli -hf rovdetection/code-1b-chat-v2-gguf:Q4_K_MBuild 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 rovdetection/code-1b-chat-v2-gguf:Q4_K_M# Run inference directly in the terminal:
./build/bin/llama-cli -hf rovdetection/code-1b-chat-v2-gguf:Q4_K_MUse Docker
docker model run hf.co/rovdetection/code-1b-chat-v2-gguf:Q4_K_MQuick Links
code-1b-chat-v2 GGUF
GGUF quantization of rovdetection/code-1b-chat-v2.
Available files
| File | Quant | Size | Use case |
|---|---|---|---|
code-1b-chat-v2-Q4_K_M.gguf |
Q4_K_M | ~700 MB | Recommended — best quality/speed |
Usage with llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="rovdetection/code-1b-chat-v2-gguf",
filename="code-1b-chat-v2-Q4_K_M.gguf",
n_ctx=2048,
)
SYSTEM = "Below is an instruction that describes a coding task. Write a response that appropriately completes the request."
prompt = f"{SYSTEM}\n\n### Instruction:\nWrite a fibonacci function.\n\n### Response:\n"
out = llm(prompt, max_tokens=200, temperature=0.7, stop=["### Instruction:"])
print(out["choices"][0]["text"])
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Model tree for rovdetection/code-1b-chat-v2-gguf
Base model
openai-community/gpt2 Finetuned
rovdetection/code-1b-pretrain-v3 Finetuned
rovdetection/code-1b-chat-v2
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf rovdetection/code-1b-chat-v2-gguf:Q4_K_M# Run inference directly in the terminal: llama cli -hf rovdetection/code-1b-chat-v2-gguf:Q4_K_M