CSGO Coach Mia, Finetuned on mistralai/Mistral-7B-Instruct-v0.2

Sample usage :

from huggingface_hub import hf_hub_download 
from llama_cpp import Llama
import torch


# Specify the path to your .gguf file
model_path = '/content/finetuned8b/finetuned8b.Q5_K_M.gguf'

# Instantiate the Llama model
llm = Llama(model_path=model_path)

prompt = "Coach Mia, help me with aiming "


## Generation kwargs
generation_kwargs = {
    "max_tokens":200,
    "stop":'[INST]',
    "echo":False, # Echo the prompt in the output
    "top_k":1 # This is essentially greedy decoding, since the model will always return the highest-probability token. Set this value > 1 for sampling decoding
}

res = llm(prompt, **generation_kwargs)



## Unpack and the generated text from the LLM response dictionary and print it
print(res["choices"][0]["text"])
# res is short for result

#output 

100% accuracy. [/INST] Aiming is a crucial aspect of CS:GO. Let's start by analyzing your sensitivity settings and crosshair placement. We can also run some aim training drills to improve your precision.