Vui Seng Chua vuiseng9

import os
import logging as log
from openvino.runtime import Core, PartialShape, serialize

log.info = print

def get_input_output_names(ports):
    return [port.any_name for port in ports]

Setup

pip install transformers torch
git clone https://huggingface.co/EleutherAI/gpt-j-6b # depends on git-lfs

Run following as python script

from transformers import AutoTokenizer, pipeline

cheatsheet

# based on following
https://github.com/openvinotoolkit/openvino/wiki/BuildingForLinux
(new) https://github.com/openvinotoolkit/openvino/blob/master/docs/dev/build_linux.md

# create conda env and activate environment (optional but recommended, use python 3.8/3.9)

git clone https://github.com/openvinotoolkit/openvino
# checkout tag or commit according

From

https://community.atlassian.com/t5/Jira-Core-Server-questions/how-to-find-all-issues-i-am-watching/qaq-p/2332

watcher = currentUser() AND resolution = Unresolved ORDER BY priority DESC, updated DESC

Install

git clone https://github.com/bigcode-project/bigcode-evaluation-harness
pip install -e .

Deterministic Generation

mistralai/Mistral-7B-v0.1 should result in "pass@1": 0.29878 paper: 30.5%, 0.7% gap

accelerate launch $WORKDIR/main.py \

import warnings
from transformers import AutoTokenizer

class PromptCreator:
    def __init__(self, model_id):
        self.tokenizer = AutoTokenizer.from_pretrained(model_id)
        self.offset = len(self.tokenizer(self.tokenizer.special_tokens_map['bos_token'])['input_ids'])
        self.samples = [
                                {

	#!/bin/sh

	set -e

	# Auto-Get the latest commit sha via command line.
	get_latest_release() {
	tag=$(curl --silent "https://api.github.com/repos/${1}/releases/latest" \| # Get latest release from GitHub API
	grep '"tag_name":' \| # Get tag line
	sed -E 's/."([^"]+)"./\1/' ) # Pluck JSON value

	# Openvino==2022.1.0
	import sys

	from openvino.runtime import Core

	DELIMITER = ' \| '

	if len(sys.argv) < 3:
	print("Please provide path to model xml file as a first arg and"
	" path to output text file to dump model constants.")

	import os
	from huggingface_hub import snapshot_download

	REPO_ID = "repo_id"
	LOCAL_ROOT= "/hf-model"
	LOCAL_DIR = os.path.join(LOCAL_ROOT, os.path.basename(REPO_ID))

	snapshot_download(repo_id=REPO_ID, local_dir=LOCAL_DIR, local_dir_use_symlinks=False)

	*.pyc
	.pytest_cache