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from pathlib import Path
from tempfile import TemporaryDirectory
import gradio as gr
from huggingface_hub import HfApi, Repository
from huggingface_hub.utils import RepositoryNotFoundError
from convert import convert
def run(
token: str, model_id: str, precision: str, quantization: bool, destination: str
) -> str:
if token == "" or model_id == "":
return """
### Invalid input 🐞
Please fill a token and model_id.
"""
if destination == "":
destination = model_id
api = HfApi(token=token)
try:
# TODO: make a PR to bloomz.cpp to be able to pass a token
api.model_info(
repo_id=model_id, token=False
) # only public repos are accessible
except RepositoryNotFoundError:
return f"""
### Error 😒😒😒
Repository {model_id} not found. Only public models are convertible at the moment.
"""
try:
with TemporaryDirectory() as cache_folder:
model_path = convert(
cache_folder=Path(cache_folder),
model_id=model_id,
precision=precision,
quantization=quantization,
)
print("[model_path]", model_path)
commit_info = api.upload_file(
repo_id=destination,
path_or_fileobj=model_path,
path_in_repo=model_path.name,
create_pr=True,
commit_message=f"Add {model_path.name} from bloomz.cpp converter.",
)
return f"""
### Success πŸ”₯
Yay! This model was successfully converted and a PR was open using your token, here:
# [{commit_info.pr_url}]({commit_info.pr_url})
"""
except Exception as e:
return f"""
### Error 😒😒😒
{e}
"""
DESCRIPTION = """
The steps are the following:
- Paste your HF token. You can create one in your [settings page](https://huggingface.co/settings/tokens).
- Input a model id from the Hub. This model must be public.
- Choose which precision you want to use (default to FP16).
- (optional) Opt-in for 4-bit quantization.
- (optional) By default a PR to the initial repo will be created. You can choose a different destination repo if you want. The destination repo must exist.
- Click Submit:
That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR πŸ”₯
"""
demo = gr.Interface(
title="Convert any BLOOM-like model to be compatible with bloomz.cpp",
description=DESCRIPTION,
allow_flagging="never",
article="Check out the [bloomz.cpp](https://github.com/NouamaneTazi/bloomz.cpp) repo on GitHub",
inputs=[
gr.Text(max_lines=1, label="your hf_token"),
gr.Text(max_lines=1, label="model_id (e.g.: bigscience/bloomz-7b1)"),
gr.Radio(choices=["FP16", "FP32"], label="Precision", value="FP16"),
gr.Checkbox(value=False, label="4-bits quantization"),
gr.Text(max_lines=1, label="destination (e.g.: my-username/bloomz-7b1.cpp)"),
],
outputs=[gr.Markdown(label="output")],
fn=run,
).queue()
demo.launch()