GGUF

Usage

from llama_cpp import Llama
from typing import Optional
import time
from huggingface_hub import hf_hub_download

def generate_prompt(input_text: str, instruction: Optional[str] = None) -> str:
    text = f"### Question: {input_text}\n\n### Answer: "
    if instruction:
        text = f"### Instruction: {instruction}\n\n{text}"
    return text

# Set up the parameters
repo_id = "vdpappu/gemma2_coding_assistant_gguf"
filename = "gemma2_coding.gguf"
local_dir = "."

downloaded_file_path = hf_hub_download(repo_id=repo_id, filename=filename, local_dir=local_dir)
print(f"File downloaded to: {downloaded_file_path}")

# Load the model 
llm = Llama(model_path=downloaded_file_path) #1 is thug
question = "Develop a Python program to clearly understand the concept of recursion."
prompt = generate_prompt(input_text=question)

start = time.time()
output = llm(prompt, 
             temperature=0.7,
             top_p=0.9,
             top_k=50,
             repeat_penalty=1.5,
             max_tokens=200, 
             stop=["Question:","<eos>"])
end = time.time()
print(f"Inference time: {end-start:.2f} seconds \n")
print(output['choices'][0]['text'])
Downloads last month
14
GGUF
Model size
2.51B params
Architecture
gemma
Hardware compatibility
Log In to view the estimation

We're not able to determine the quantization variants.

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Dataset used to train vdpappu/gemma2_coding_assistant_gguf