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CPU Upgrade
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import json
import os
import pprint
from datetime import datetime, timezone
import click
from colorama import Fore
from huggingface_hub import HfApi, snapshot_download
from src.submission.check_validity import get_model_size
from src.display.utils import ModelType, WeightType, Language
from src.submission.submit import add_new_eval
from src.envs import EVAL_REQUESTS_PATH, QUEUE_REPO
precisions = ("float16", "bfloat16", "8bit (LLM.int8)", "4bit (QLoRA / FP4)", "GPTQ")
model_types = [e.name for e in ModelType]
weight_types = [e.name for e in WeightType]
language_types = [e.name for e in Language]
def main():
api = HfApi()
current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
snapshot_download(repo_id=QUEUE_REPO, revision="main", local_dir=EVAL_REQUESTS_PATH, repo_type="dataset")
model_name = click.prompt("Enter model name")
revision = click.prompt("Enter revision", default="main")
precision = click.prompt("Enter precision", default="float16", type=click.Choice(precisions))
model_type = click.prompt("Enter model type", type=click.Choice(model_types))
weight_type = click.prompt("Enter weight type", default="Original", type=click.Choice(weight_types))
base_model = click.prompt("Enter base model", default="")
main_language = click.prompt("Enter language type", default="English", type=click.Choice(language_types))
try:
model_info = api.model_info(repo_id=model_name, revision=revision)
except Exception as e:
print(f"{Fore.RED}Could not find model info for {model_name} on the Hub\n{e}{Fore.RESET}")
return 1
if click.confirm("Do you want to continue? This request file will be pushed to the hub"):
click.echo("continuing...")
print(add_new_eval(
model=model_name,
base_model=base_model,
revision=revision,
precision=precision,
private=False,
weight_type=weight_type,
model_type=model_type,
main_language=main_language,
source="manual"
))
else:
click.echo("aborting...")
if __name__ == "__main__":
main()
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