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.
