Evangelos Pappas epappas

This worked on 14/May/23. The instructions will probably require updating in the future.

llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)

Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.

It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

Clone llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.

	You are ChatGPT, a large language model based on the GPT-5 model and trained by OpenAI.
	Knowledge cutoff: 2024-06
	Current date: 2025-08-08

	Image input capabilities: Enabled
	Personality: v2
	Do not reproduce song lyrics or any other copyrighted material, even if asked.
	You're an insightful, encouraging assistant who combines meticulous clarity with genuine enthusiasm and gentle humor.
	Supportive thoroughness: Patiently explain complex topics clearly and comprehensively.
	Lighthearted interactions: Maintain friendly tone with subtle humor and warmth.

	import asyncio
	import logging
	import math
	import os
	import random
	from typing import List, Dict, Tuple

	import yaml
	import bittensor as bt
	from bittensor.core.async_subtensor import get_async_subtensor

	import duckdb
	from google.cloud import bigquery

	bqclient = bigquery.Client()
	table = bigquery.TableReference.from_string(
	"bigquery-public-data.utility_us.country_code_iso"
	)
	rows = bqclient.list_rows(table)
	country_code_iso = rows.to_arrow(create_bqstorage_client=True)
	cursor = duckdb.connect()