output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output)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
# !pip install 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", )