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"""
download_model.py
- Paste your Hugging Face token into HUGGINGFACE_TOKEN below.
- By default it will try to download from REPO_ID and only files matching PATTERN.
- It prints the path of the downloaded .gguf file on success.
"""
import os
import glob
from huggingface_hub import login, snapshot_download
# ---- EDIT: paste your token here (or set HUGGINGFACE_TOKEN env var) ----
HUGGINGFACE_TOKEN = "hf_XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
# -----------------------------------------------------------------------
# Replace with the repo that contains your GGUF files (change if needed)
REPO_ID = "unsloth/gpt-oss-20b-GGUF"
LOCAL_DIR = "models/oss_20b_gguf"
# Pattern to fetch only the Q2_K_L weight file:
PATTERN = "*Q2_K_L.gguf"
if not HUGGINGFACE_TOKEN or HUGGINGFACE_TOKEN.startswith("PASTE_"):
raise SystemExit("Please paste your Hugging Face token into HUGGINGFACE_TOKEN variable in this file.")
print("Logging in to Hugging Face hub...")
login(token=HUGGINGFACE_TOKEN)
print(f"Downloading from repo: {REPO_ID} --> local dir: {LOCAL_DIR}")
path = snapshot_download(
repo_id=REPO_ID,
local_dir=LOCAL_DIR,
token=HUGGINGFACE_TOKEN,
allow_patterns=[PATTERN],
resume_download=True,
)
# find the downloaded .gguf file
candidates = glob.glob(os.path.join(LOCAL_DIR, "**", "*.gguf"), recursive=True)
candidates = [c for c in candidates if "Q2_K_L" in os.path.basename(c)]
if not candidates:
raise SystemExit("Download finished but no Q2_K_L.gguf found in the target folder. Check REPO_ID or PATTERN.")
gguf_path = os.path.abspath(candidates[0])
print("Download complete.")
print("GGUF model path:", gguf_path)
print("\nSet MODEL_PATH in app.py to this path (or leave app.py to auto-detect 'models/**/*.gguf').")
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