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pedro-dev (#22)
Browse files- Fix cache removal (8d4ed6d0cc348fb02dec4066ea6aa71a5431df92)
- Set cache to a directory (383d050be2c87b73393c15023504f8e5e39e31bd)
- Convert (d5eb6e15f92173e93a9b26dbe3a935d3431c3a1c)
- Cleanup (2c3ad17d2dccee44bc09c71183dc58e1f590c06f)
- Apply quant method (dcd5ecd654cf9067d7f1efe272fe9ae6351602e5)
Co-authored-by: Pedro Cuenca <[email protected]>
- app.py +22 -28
- cache/.keep +0 -0
- converted/.keep +0 -0
app.py
CHANGED
@@ -1,20 +1,17 @@
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import os
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import
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os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
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import gradio as gr
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from huggingface_hub import
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from huggingface_hub import snapshot_download
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from huggingface_hub import whoami
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from huggingface_hub import ModelCard
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from huggingface_hub import login
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from huggingface_hub import scan_cache_dir
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from huggingface_hub import logging
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from gradio_huggingfacehub_search import HuggingfaceHubSearch
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from apscheduler.schedulers.background import BackgroundScheduler
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from textwrap import dedent
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@@ -22,23 +19,24 @@ from textwrap import dedent
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import mlx_lm
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from mlx_lm import convert
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from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
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HF_TOKEN = os.environ.get("HF_TOKEN")
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def clear_hf_cache_space():
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scan = scan_cache_dir()
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to_delete = []
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for repo in scan.repos:
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if repo.repo_type == "model":
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to_delete.
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scan.delete_revisions(to_delete)
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print("Cache has been cleared")
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def upload_to_hub(path, upload_repo, hf_path, token):
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card = ModelCard.load(hf_path)
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card.data.tags = ["mlx"] if card.data.tags is None else card.data.tags + ["mlx"]
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card.data.base_model = hf_path
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@@ -86,33 +84,29 @@ def upload_to_hub(path, upload_repo, hf_path, token):
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)
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print(f"Upload successful, go to https://huggingface.co/{upload_repo} for details.")
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def process_model(model_id, q_method,oauth_token: gr.OAuthToken | None):
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if oauth_token.token is None:
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raise ValueError("You must be logged in to use MLX-my-repo")
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model_name = model_id.split('/')[-1]
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print(model_name)
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username = whoami(oauth_token.token)["name"]
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print(username)
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# login(token=oauth_token.token, add_to_git_credential=True)
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try:
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upload_repo = username
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print(upload_repo)
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return (
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f'Find your repo <a href
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"llama.png",
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)
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except Exception as e:
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return (f"Error: {e}", "error.png")
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finally:
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shutil.rmtree("mlx_model", ignore_errors=True)
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clear_hf_cache_space()
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print("Folder cleaned up successfully!")
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import os
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import tempfile
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os.environ["HF_HUB_CACHE"] = "cache"
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os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
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import gradio as gr
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from huggingface_hub import HfApi
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from huggingface_hub import whoami
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from huggingface_hub import ModelCard
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from huggingface_hub import scan_cache_dir
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from huggingface_hub import logging
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from gradio_huggingfacehub_search import HuggingfaceHubSearch
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from apscheduler.schedulers.background import BackgroundScheduler
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from textwrap import dedent
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import mlx_lm
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from mlx_lm import convert
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HF_TOKEN = os.environ.get("HF_TOKEN")
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# I'm not sure if we need to add more stuff here
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QUANT_PARAMS = {
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"Q4": 4,
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"Q8": 8,
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}
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def clear_hf_cache_space():
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scan = scan_cache_dir()
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to_delete = []
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for repo in scan.repos:
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if repo.repo_type == "model":
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to_delete.extend([rev.commit_hash for rev in repo.revisions])
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scan.delete_revisions(*to_delete).execute()
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print("Cache has been cleared")
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def upload_to_hub(path, upload_repo, hf_path, token):
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card = ModelCard.load(hf_path)
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card.data.tags = ["mlx"] if card.data.tags is None else card.data.tags + ["mlx"]
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card.data.base_model = hf_path
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)
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print(f"Upload successful, go to https://huggingface.co/{upload_repo} for details.")
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def process_model(model_id, q_method, oauth_token: gr.OAuthToken | None):
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if oauth_token.token is None:
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raise ValueError("You must be logged in to use MLX-my-repo")
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model_name = model_id.split('/')[-1]
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username = whoami(oauth_token.token)["name"]
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try:
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upload_repo = f"{username}/{model_name}-{q_method}-mlx"
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print(upload_repo)
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with tempfile.TemporaryDirectory(dir="converted") as tmpdir:
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# The target dir must not exist
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mlx_path = os.path.join(tmpdir, "mlx")
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convert(model_id, mlx_path=mlx_path, quantize=True, q_bits=QUANT_PARAMS[q_method])
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print("Conversion done")
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upload_to_hub(path=mlx_path, upload_repo=upload_repo, hf_path=model_id, token=oauth_token.token)
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print("Upload done")
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return (
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f'Find your repo <a href="https://hf.co/{upload_repo}" target="_blank" style="text-decoration:underline">here</a>',
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"llama.png",
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)
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except Exception as e:
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return (f"Error: {e}", "error.png")
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finally:
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clear_hf_cache_space()
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print("Folder cleaned up successfully!")
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cache/.keep
ADDED
File without changes
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converted/.keep
ADDED
File without changes
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