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.